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Team EQUIS i FRR v1.0

HASP Program

Flight Readiness Review Document for the Attitude Determination System (ADS)

Experiment by Experiments with Quality United In Science

(EQUIS)

Prepared by: Team Leader: Dr. H. B. Vo/E.G.Delgado 7/23/2010

Team Member: A. M. Espinal Mena 7/23/2010

Team Member: F. O. Rivera Vélez 7/23/2010

Team Member: E.M. Portilla Matías 7/23/2010

Team Member: J. I. Espinosa Acevedo 7/23/2010

Submitted:

Reviewed:

Revised:

Approved: Dr. Greg Guzik 7/23/2010

Institution Signoff Date

HASP Signoff Date

Team EQUIS ii FRR v1.0

Change Information Page

Title: FRR Document for ADS Experiment Date: 07/23/2010

List of Effected Pages

Page Number Issue Date

Team EQUIS iii FRR v1.0

Status of TBDs

TBD

Number

Section Description Date

Created

Date

Resolved

Team EQUIS iv FRR v1.0

Table of Contents Experiment by .............................................................................................................................. i

Change Information Page ........................................................................................................... ii

Status of TBDs ...........................................................................................................................iii

Table of Contents ....................................................................................................................... iv

List of Figures ............................................................................................................................ vi

List of Tables ...........................................................................................................................viii

1.0 Document Purpose ................................................................................................................ 9

1.1 Document Scope ............................................................................................................... 9

1.2 Change Control and Update Procedures ........................................................................... 9

2.0 Reference Documents ........................................................................................................... 9

3.0 Goals, Objectives, Requirements ........................................................................................ 11

3.1 Mission Goal ................................................................................................................... 11

3.2 Objectives ....................................................................................................................... 11

3.3 Science Background and Requirements.......................................................................... 12

3.4 Technical Background and Requirements ...................................................................... 25

4.0 Payload Design ................................................................................................................... 30

4.1 Principle of Operation ..................................................................................................... 30

4.2 System Design ................................................................................................................ 30

4.3 Electrical Design ............................................................................................................. 37

4.4 Software Design .............................................................................................................. 44

4.5 Thermal Design ............................................................................................................... 50

4.6 Mechanical Design.......................................................................................................... 52

5.0 Payload Development Plan ................................................................................................. 58

6.0 Payload Construction Plan .................................................................................................. 59

6.1 Hardware Fabrication and Testing .................................................................................. 59

6.2 Integration Plan ............................................................................................................... 59

6.3 Software Implementation and Verification ..................................................................... 60

6.4 Flight Certification Testing ............................................................................................. 61

7.0 Mission Operations ............................................................................................................. 63

7.1 Pre-Launch Requirements and Operations ..................................................................... 63

7.2 Flight Requirements, Operations and Recovery ............................................................. 70

7.3 Data Acquisition and Analysis Plan ............................................................................... 70

8.0 Project Management ........................................................................................................... 71

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8.1 Organization and Responsibilities .................................................................................. 71

8.2 Configuration Management Plan .................................................................................... 71

8.3 Interface Control ............................................................................................................. 71

9.0 Master Schedule .................................................................................................................. 72

9.1 Work Breakdown Structure (WBS) ................................................................................ 72

9.2 Staffing Plan.................................................................................................................... 72

9.3 Timeline and Milestones ................................................................................................. 73

10.0 Master Budget ................................................................................................................... 73

10.1 Expenditure Plan ........................................................................................................... 73

11.0 Risk Management and Contingency ................................................................................. 74

12.0 Glossary ............................................................................................................................ 76

Appendix ................................................................................................................................... 77

Appendix A ........................................................................................................................... 77

Appendix B ........................................................................................................................... 80

Sensors Subsystem Schematic and PCB design ............................................................... 80

Appendix C ........................................................................................................................... 82

RTC (DS1306) pseudo code ............................................................................................. 82

Magnetometer (MicroMag3) pseudo code ........................................................................ 83

Accelerometer (SCA3000-D01) pseudo code ................................................................. 85

SD card pseudo code ......................................................................................................... 86

Pre-flight software ............................................................................................................ 87

During flight software ....................................................................................................... 91

Appendix D ......................................................................................................................... 103

Team EQUIS vi FRR v1.0

List of Figures

Figure 1: Three axis center mass reference frame and their rotational change definition ........ 13 Figure 2: Accelerometer average values ................................................................................... 14 Figure 3: Accelerometer maximum values ............................................................................... 14 Figure 4: Gyroscope basic structure and operation ................................................................... 15

Figure 5: Earth's Magnetic Field ............................................................................................... 16 Figure 6: Magnitude of the earth’s magnetic field .................................................................... 17 Figure 7: Parameters of the magnetic field ............................................................................... 17 Figure 8: Vector's example of the magnetic field ..................................................................... 18 Figure 9: Vector’s example of the magnetic field .................................................................... 18

Figure 10: Angles of interest ..................................................................................................... 19 Figure 11: HASP 2006 flight profile ........................................................................................ 20

Figure 12: Payload trajectory dynamics ................................................................................... 20 Figure 13: Angle of translation determination .......................................................................... 21 Figure 14: Angle of translation determination .......................................................................... 21 Figure 15 Beamwidth shade diameter determination ............................................................... 21

Figure 16: Determining position accuracy ................................................................................ 22 Figure 17: Determining position accuracy with orbit decay ..................................................... 22 Figure 18: Plot of typical orbit decay ....................................................................................... 23

Figure 19: Temperature variation during flight ........................................................................ 24 Figure 20: Accelerometers basic principal of operation ........................................................... 25

Figure 21: Gyroscopes basic principal of operation ................................................................. 26 Figure 22: Simplified representation of magnetometer basic operations ................................. 27 Figure 23: The DS18B20 Digital temperature sensor............................................................... 28

Figure 24: DS18B20 Digital Temperature Sensor Diagram (From the DS18B20 datasheet) .. 28

Figure 25: Determination of sampling rate by maximum angular velocity .............................. 29 Figure 26: ADS System Design ................................................................................................ 30 Figure 27: Arduino Pro 328 3.3V/8MHz schematic ................................................................. 31

Figure 28: Three Axis Accelerometer schematic ...................................................................... 31 Figure 29: Three Axis Magnetometer schematic ...................................................................... 32

Figure 30: Three Axis Gyroscope schematic ............................................................................ 32 Figure 31: Digital Temperature Sensor schematic .................................................................... 32 Figure 32: MicroSD board schematic ....................................................................................... 33 Figure 33: Real-Time Clock schematic .................................................................................... 33

Figure 34: 9V DC to DC Converter schematic ......................................................................... 33 Figure 35: 3.3V Voltage Regulator schematic .......................................................................... 34 Figure 36: 5V Voltage Regulator schematic ............................................................................. 34

Figure 37: Electrical Design Subsystems ................................................................................. 37 Figure 38: Electrical Subsystem ............................................................................................... 37 Figure 39: Accelerometer Sensor.............................................................................................. 38 Figure 40: SCA3000 Three axis accelerometer pins ................................................................ 38

Figure 41: Gyroscope Sensor .................................................................................................... 39 Figure 42: Three Axis Magnetometer ....................................................................................... 39 Figure 43: Digital Temperature Sensor ..................................................................................... 39

Figure 44: Real Time Clock ...................................................................................................... 40

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Figure 45: ADS PCB Design .................................................................................................... 41

Figure 46: Power System Diagram ........................................................................................... 42 Figure 47: Power Budget Analysis ........................................................................................... 44 Figure 48: Flight software control flow chart ........................................................................... 49

Figure 49:Payload”s Top Cover ................................................................................................ 53 Figure 50: Internal View of the External Structure .................................................................. 54 Figure 51: External Structure Drawing ..................................................................................... 54 Figure 52: Finite Element Analysis View 1 .............................................................................. 55 Figure 53 Finite Element Analysis View 2 ............................................................................... 55

Figure 54: Detail drawings of payload...................................................................................... 56 Figure 55: Top view payload structure ..................................................................................... 56 Figure 56: View of punctures on structures .............................................................................. 57 Figure 57: Internal Structure Drawing ...................................................................................... 57

Figure 58: EDAC pin layout ..................................................................................................... 60 Figure 59 Psi Vacuum chamber ................................................................................................ 61

Figure 60 Chamber where temperature test was taken ............................................................. 62 Figure 61: Shock Test ............................................................................................................... 62

Figure 62 Helmholtz coils ......................................................................................................... 64 Figure 63: Helmholtz coil (X) vs MM3 (Y) ............................................................................. 66 Figure 64: Linear Fit ................................................................................................................. 69

Figure 65: WBS- Work Breakdown Schedule .......................................................................... 72 Figure 66: Risk Management Cycle ......................................................................................... 75

Figure 68: Heat Loss Analysis .................................................................................................. 77 Figure 69: External Convention ................................................................................................ 79

Team EQUIS viii FRR v1.0

List of Tables

Table 1: Traceability Matrix ..................................................................................................... 36 Table 2: Pins for the Pro 328 .................................................................................................... 40 Table 3: Power Requirements ................................................................................................... 43 Table 4: Bytes Description........................................................................................................ 45

Table 5: SPCR bit specification ................................................................................................ 46 Table 6: RTC registers and address map .................................................................................. 46 Table 7: Axis Select .................................................................................................................. 47 Table 8: SCA3000 registers ...................................................................................................... 47 Table 9: Electronic temperature limits ...................................................................................... 50

Table 10: Effects of the surface treatment in the emisivity ...................................................... 52 Table 11: Alloy Selection ......................................................................................................... 52

Table 12 Polyester Properties ................................................................................................... 57 Table 13: Mass Budget ............................................................................................................. 58 Table 14: EDAC 516 pins function and color code .................................................................. 60 Table 15 Example of raw data from the MM3 ......................................................................... 65

Table 16: Calibration values ..................................................................................................... 65 Table 17: Equations to correct offset ........................................................................................ 65 Table 18: Quadrant determination ........................................................................................... 66

Table 19: DS18B20 versus HOBO temperature measures ....................................................... 68 Table 20: Materials Acquirement & Costs ............................................................................... 74

Table 21: Risk Management & Contingency............................................................................ 75

Team EQUIS 9 FRR v1.0

1.0 Document Purpose

This document describes the final designs for the Attitude Determination System (A.D.S.)

experiment by Team EQUIS for the HASP Program. It fulfills part of the HASP Project

requirements for the Flight Readiness Review (FRR) to be held July 23, 2010.

1.1 Document Scope

This FRR document specifies the scientific purpose and requirements for the A.D.S.

experiment and provides a guideline for the development, operation, and cost of this payload

under the HASP Project. The document includes details of the payload design, fabrication,

integration, testing, flight operation, and data analysis. In addition, project management,

timelines, work breakdown, expenditures, and risk management is discussed. Finally, the

designs and plans presented here are preliminary.

1.2 Change Control and Update Procedures

Changes to this FRR document shall only be made after approval by designated

representatives from Team EQUIS and the HASP Institution Representative. Document

modification requests should be sent to Team members, the HASP Institution Representative

and the HASP Project.

2.0 Reference Documents

The following websites are references for relevant scientific information as well as sources of

electronic components, their specifications, part numbers, products availability, and prices.

Bibliography:

[1] (USRA), R. N. (2002, November 25). Astronomy Picture of the Day. Retrieved May

24, 2010, from Astronomy Picture of the Day Web site:

http://www.astronet.ru/db/xware/msg/1181025

[2] Analog Devices Corporate Headquarters. (2008, September). Analog Devices.

Retrieved May 24, 2010, from Analog Devices Web site: http://www.analog.com

[3] Arduino Pro. (2010). Retrieved March 28, 2010, from Arduino:Blog:

http://arduino.cc/en/Main/ArduinoBoardPro, March 28, 2010

[4] Biology Blog. (n.d.). Retrieved May 24, 2010, from Biology Blog Web Site:

http://www.biology-blog.com/blogs/permalinks/7-2007/chickens-and-earths-magnetic-

field.html

[5] Field Code. (2008). Retrieved February 3, 2010, from Whatis?com Web site:

http://whatis.techtarget.com/definition/0,,sid9_gci213703,00.html

[6] kowoma.de. (2009, April 19). Retrieved May 24, 2010, from kowoma.de Web site:

http://www.kowoma.de/en/gps/additional/atmosphere.htm


[7] Metrolab Instruments. (2006, October). Metrolab Instruments. Retrieved May 24,

2010, from MetroLab Manufactures of MRI systems:

http://www.metrolab.com/index.php?id=10

[8] Mystery Class. (2008). Retrieved May 24, 2010, from Mystery Class Journy North

Web site: http://www.learner.org/jnorth/tm/mclass/Glossary.html

[9] Ritter, M. E. (2009). The Physical Environment an Introduction to Physical

Geography. Retrieved May 24, 2010, from

http://www.uwsp.edu/geo/faculty/ritter/geog101/textbook/energy/earth_sun_relations_

seasons.html

[10] Sparkfun. (2003). Retrieved May 24, 2010, from Sparkfun website:

http://www.sparkfun.com

[11] Wikipedia (DC-to-DC Converters). (2010). Retrieved April 4, 2010, from Wikipedia

Web site: http://en.wikipedia.org/wiki/DC-to-DC_converter

[12]Anderson, B. J., editor, and R. E. Smith, compiler, Natural Orbital Environment

Guidelines for Use in Aerospace Vehicle Development, NASA TM 4527, chapters 6

and 9, June 1994.

[13] T Williams & P Collins, 1997, "Orbital Considerations in Kankoh-Maru Rendezvous

Operations", Proceedings of 7th ISCOPS, AAS Vol 96, pp 693-707.

http://en.wikipedia.org/wiki/DC-to-DC_converter


3.0 Goals, Objectives, Requirements

3.1 Mission Goal

The goal of this project is to develop an attitude determination systems (ADS) prototype, by

improving the robustness and accuracy of a previous design (ABITA; Tiger team) in order to

obtain relevant data and hands-on experience for a future satellite attitude control and

determination system (ADCS). The designing, developing and testing will serve as a stepping

stone for a future CubeSat project with the objective to transmit to a ground station the

measurement data that has been applied for the terrestrial gamma ray flashes (TGF).

Previous CubeSat data will help as a base point for this design.

3.2 Objectives

3.2.1 Science Objectives

There are four science objectives related to this ADS experiment which are the following:

1. To determine translation and attitude motion of the payload during flight.

2. To obtain the platform’s body frame orientation with respect to the body fixed reference

frame

3. To measure the Earth’s gravitational and magnetic field and the angular momentum of the

payload such that the data can be used to determine the orientation of the payload.

4. To measure the heat transfer characteristic during flight and its potential impact on internal

and structural components.

This attitude information will demonstrate the robustness and effectiveness expected from the

proposed requirements for the payload described in this document for tracking purposes. Post

processing of this data will confirm the assumption presented in this work to design similar

ADS for future small satellite missions.

3.2.2 Technical Objectives

There are technical objectives that are required to learn during this experience. These

objectives will be completed during the development of the attitude determination system:

1. Design and connect the sensors such that they can be located in the body frame of the

payload to fully determine the attitude motion of the payload.

2. Use different attitude determination algorithms used to determine the attitude motion

of the payload such as the Kalman Filter, QUEST and TRIAD to be used as the

algorithms to determine the attitude motion

3. Develop graphs and charts related to the translation and orientation of the vehicle as

well as the heat transfer in it

4. Reduce the attitude pointing knowledge of the payload to less than 10 degrees of error.


These objectives provide the desire knowledge to learn how the attitude determination

system can be used in an actual mission.

3.3 Science Background and Requirements

3.3.1 Science Background

The design of the attitude determination system (ADS) for this payload is a midpoint

development for a future CubeSat project with the purpose of communicating data about

measurements for science missions such as a terrestrial gamma ray flashes (short blasts of

gamma rays, which are discharged from the uppermost part of the atmosphere into space1) or

other similar science objectives. The intended requirements must be those needed for an

effective and almost error free communication of the ADS data for the CubeSat that will be

navigating at a height above the Earth’s surface as well as the design of the communication

system with a suitable main lobe beamwidth. The A.D.S. project will give the opportunity to

enhance the chosen technology as well as determine the minimum adjustments that it might

need to meet the goal, which is to develop an attitude determination system prototype.

The attitude of a spacecraft is its orientation in space. The motion of a rigid spacecraft is

specified by its position, velocity, attitude, and attitude motion. The position, acceleration,

and velocity quantities describe the translational motion of the center of mass of the spacecraft

and can be determined from previously defined spatial frames such as the magnetic field of

the Earth and the moment of inertia of the body itself. Moreover, attitude determination is

used to change the spacecraft’s direction and maintain the spacecraft on-course (Attitude

Control System).

Attitude analysis can be classified in three types: attitude determination, prediction, and

control. Attitude determination is a process of calculating the orientation of an object relative

to an inertial reference frame. Attitude prediction is the process of anticipating the future

course of the object through the analysis of dynamic models to extrapolate the attitude history.

Attitude control is the method of controlling the orientation of the object based on a

predetermined data from the sensors; it consists of two areas of control, attitude stabilization

and maneuver control, for example a CubeSat project.

The orientation of the payload will be determined by comparing its actual three axis body

frame (three dimensional orthogonal axes at the payload center of mass) with those of three

external vector fields: the Earth’s gravitational field, the payload angular momentum, and the

Earth’s magnetic field.

The gravitational field will serve as a reference frame to measure the change of position,

velocity and acceleration of the payload. The gravitational field has a constant direction

(towards the Earth’s center) which allows its use as a trusted reference frame. The change of

the payload’s center of mass with respect to the Earth’s gravitational frame is done by

determining the yaw, pitch, and roll of the payload when its acceleration is determined with

1 The gamma rays are presumed to be released by electrons traveling at the speed of light when they scatter off

of atoms and decelerate. The mechanism in which the electrons produce TGFs is uncertain; although, it

probably involves the build-up of electric charge at the tops of clouds due to lightning discharge. This results in

a powerful electric field between the top of the clouds and the ionosphere. (Tim Stephens, UC at Santa

Cruz,2005)


respect to the gravitational field. A single integration of the acceleration will have a result of

the payload’s velocity (a vector) and a double integration will result in the payload’s position

with respect to a previous measured point (previous state or reference starting point).

Figure 1: Three axis center mass reference frame and their rotational change definition

Figure 1 illustrates the rotational movements (roll, pitch, and yaw), which are described in

reference to a plane. The movement described is a combination of two-axis (2 dimensional)

area and a missing combination of a pair of axis (pitch) is portrayed in the z – y plane. The

acceleration with respect to the gravitational field will determine the proper acceleration,

which is the acceleration “detected” by the payload within the reference gravitational field.

For example, the gravitational field strength is 1g; the proper acceleration of the payload must

be obtained by subtracting this 1g to that acceleration sensed. If the velocity is constant the

proper acceleration is zero (0).

The ABITA project (2008), determined the balloon dynamics during flight by doing the

following: comparing acceleration vs. altitude, rotational rate, and translational movement of

the payload. The ABITA payload used the gravitational field to determine its acceleration. A

known disadvantage of using the aforementioned is that it needs another frame to initialize the

spatial model (such as data from a GPS). As a brief description of its basic operation, to

measure acceleration is to determine the vibration, or acceleration of motion of a structure.


Figure 2: Accelerometer average values

As it is observed from Figure 2 the average maximum and minimum acceleration that was

achieved by the ABITA was approximately 1.6g and -1.2g, respectively. The values shown

on Figure 3, repeat at 3g, thus it is considered the maximum average.

Figure 3: Accelerometer maximum values

In conjunction with measuring the acceleration, the measurement of the moment of inertia is

used to determine accurately the attitude of the payload. The angular momentum of the

payload and its rate of change, with respect to time, provide information of the payload’s

orientation state in a repetitive measured time frame. There is an equivalence between the

angular momentum at a specific distance from the center of a spinning body (r), the moment

of inertia (I), the angular speed (), and linear momentum (p) that a body experiments when

moving in a straight line at a known velocity (v). The moment of inertia is defined as the

resistance of a body to an angular acceleration applied to it. The resistance to the angular

acceleration, on any of the 3 rotational axes, can be measured to determine when the body is

rotating due to an external applied force. The result of the integral of an angular acceleration


is the velocity and position of the body. The initial position is obtained by using other

reference information, such as that obtained from a Global Positioning System.

A gyroscope is a device used to measure the orientation of an object in space, based on the

principles of conservation of angular momentum. The simplest way to explain the gyroscope

function is to consider the mechanical gyroscope which is essentially a spinning wheel or

disk whose axle is mounted on a metal frame and that is free to take any orientation. The

metal frame consists of three rings called gimbals. A diagram of this device is illustrated in

Figure 4. If the wheel in the center of the frame is not rotating the gyroscope behaves like

any other object with respect to gravity, but if the wheel is spinning this behavior changes.

When the wheel spins an angular momentum (L) is created with a direction collineal to the

axis of rotation. Because of the presence of the angular momentum a resistive force is created.

The resistive force resists the changes in the direction of the wheel’s rotational axis if the

gyroscope is tilted or rotated. If a gyroscope is tipped, the gimbals will try to reorient to keep

the spin axis of the rotor in the same direction. If released in this orientation, the gyroscope

will rotate maintainig the direction of the rotational axis (i.e. the direction of the angular

momentum), this behaivor is known as precession. Precession is a change in the orientation

of the rotation axis of a rotating body but without changing the direction of the axis.

Figure 4: Gyroscope basic structure and operation

The gyroscope commonly selected for payload projects are micro electrical mechanical

system (MEMS) gyroscopes, which detect rotational rate about the X (roll), Y (pitch), and Z

(yaw) axes. When the gyros are rotated about any of the sense axes, the Coriolis Effect causes

a deflection that is detected by a capacitive pickoff. The resulting signal is amplified,

demodulated, and filtered to produce a voltage that is proportional to the angular rate. The

Coriolis Effect is an inertial force that appears in bodies that possesses two types of motion; a

rotational motion and a linear motion. The interaction between the linear and rotational

movement produce a linear acceleration of the body in a different direction and that is known

as the Coriolis acceleration.

The use of an accelerometer and a gyroscope is essential to obtain a more precise data of the

inertial reference frame because they provide linear and rotational attitude information. Pure

gyroscopic data is used for rotation detection (angular velocity within the inertial frame) with

high resolution and quick response. Pure accelerometer data can be used for application for

fixed reference frame from gravity as well as linear or tilt movement, constrained to initial

position determination. Moreover, the data received from the accelerometer can be processed

(mathematically integrated) to obtain the velocity and position of the body from this


previously reference starting point. Having both gyroscopes and accelerometers we can obtain

the motion processing solution of linear movement and rotation at the same time. By tracking

both the current angular velocity of the system and the current linear acceleration of the body

it is possible to determine the overall attitude, position, and velocity of the body provided by a

starting reference point in time (for example, determined periodically from a GPS). The

starting point provided by the reference mechanism (GPS) provides for the minimization of

the cumulative errors inherent of a sensors system with no external reference frame used when

integration is used.

The Earth’s magnetic field is used as a reference frame for the payload in order to determine

attitude. The magnetic field exists due to the movement inside the Earth’s liquid in the outer

core (mostly compound by iron) that produces an electric current. A dynamo effect is created

and it converts the Earth to a very large bar magnet with a magnetic field that goes from the

North Pole to the South Pole associated to it. Figure 5 presents a not-to-scale representation

of the magnetic field. The HASP mainframe should rise at about 120,000 feet or

approximately 36 km navigating through the magnetic field.

Figure 5: Earth's Magnetic Field

Earth has a magnetic field tilted at about 23.5º with respect to the rotational (physical) axis.

The common sensor used to detect this magnetic field reference frame is the magnetometer.

The magnetometer that will be used for the A.D.S. project consists of three axes (x, y, and z)

that will provide a vector component. The data obtained from this device will be the magnetic

field intensity vs. typical values of the Earth’s magnetic field that goes from 30,000 nT (in the

equator) towards 60,000 nT (in the Poles). Typical values of a magnetometer suitable for this

payload are approximately ±1,000,000 nT and ±15 nT of resolution. The magnetic field vector

will be obtained by the combination of the measurements of each axis and thus can be

projected with respect to the Earth’s magnetic field to determine the payload’s orientation. In

attitude determination systems magnetometers are used because of vector sensing capabilities.

They can provide both direction and magnitude of the magnetic field.


Figure 6: Magnitude of the earth’s magnetic field

The Earth's magnetic field can be described, at any point and time by a direction and intensity

which can be measured. The Earth’s magnetic field is a vector field in which at least three

components are necessary to represent the field. Commonly the components of the

geomagnetic field that are measured are the north (X) and east (Y) components of the

horizontal intensity and the vertical intensity (Z). From these elements, all other parameter of

the magnetic field can be calculated. A figure that illustrates these parameters is the following:

Figure 7: Parameters of the magnetic field

The magnetic field’s direction is described by the declination (D) and the inclination (I).

These two parameters (i.e. D and I), are measured in units of degrees. The declination angle is

form between the magnetic north (i.e. x in the plot), and the horizontal intensity or true north.

The inclination angle is form between the horizontal intensity and the total intensity field

vector. The parameters that describe the field intensity are the total intensity (F), horizontal

component (H), vertical component (Z), and the north (X) and east (Y) components of the

horizontal intensity. These parameters are normally expressed in units of nanoTesla or gauss.

The magnetic field parameters measured are used to determine the payload’s orientation with

respect to the axis directions of the Earth’s magnetic field. (i.e. Northward Eastward and

Downward in the figure #). To explain the procedure performed to interpret the magnetometer

data in order to define the payload’s orientation let’s consider the following example:


If the magnetic field measurement obtained at one instant of time during the payload’s flight

is x=35,000nT, y=-3314nT and z=38,000nT and the data obtained for the standard value of

the magnetic field in that earth’s region is x’=31310.8nT, y’=-1174.1nT and z’=40942.2nT,

what is the payload’s orientation?

Figure 8: Vector's example of the magnetic field

In this problem the angles formed between the two systems of coordinate axis is what is

desired to be determined, since, these angles will define the payload’s orientation with respect

to the reference frame of the Earth’s magnetic field. Considering only the angle formed

between the axis z and z’ it’s found out that the angle can be define taking in to account the

projection of the component of the magnetic field in the z direction onto the z’ axis. This

procedure is illustrated in the following figure:

Figure 9: Vector’s example of the magnetic field

As illustrated above the angle between axes can be determined just by considering the

projection of the component with respect to the desired axis. This procedure is repeated until

all the axes with respect to one component are considered. To completely define the payload’s

orientation the angles formed in each axis by each component must be determined. These

angles can be determined since the values of the component of the magnetic field intensity are

known in both coordinate systems. The angles between the coordinate system that are needed

to determine the payloads orientation with respect to the Earth’s magnetic field ar shown on

Figure 10.

p = 35000 – 3314 + 38000

E = 31310.8 – 1174.1 + 40942.2

=

bz= bz’ cos Θz

Θz= cos-1

(bz/bz’)


Figure 10: Angles of interest

Therefore three equations are necessary to completely define the payload’s orientations since

three angle are needed to define the payload’s attitude. These equations are:

Θz= cos-1

(bz/bz’) Θy= cos-1

(by/by’) Θx= cos-1

(bx/bx’)

The value of the earth’s magnetic field in a certain region of the earth will be provided by

simulation software available in the International Geomagnetic Reference Field (IGRF) web

page. This simulator only request values of altitude, latitude and longitude to estimate the

magnitude and direction of the earth’s magnetic field. The latitude, longitude and altitude

information will be provided by the GPS on board the HASP platform to perform the analysis

post flight.

Post processing of the received data might include the use of mathematical and statistical

algorithms such as the Kalman Filter, to decrease substantially inherent noise in the data. This

allows predicting the real position and orientation of the payload at any moment during flight.

The Kalman Filter determines the next state estimation by using average weighted matrices

that combines the present state, a mathematical model of the measurement systems and the

noise inherent to both, the system and the measurement devices.

The position and direction of movement will be obtained by determining the payload’s current

position, velocity, and acceleration. The x(t), y(t), and z(t)) will be recorded periodically in a

pre-defined time rate for the whole flight trajectory (creating a vector matrix of its position,

x(t+nt), y(t+nt), z(t+nt), where i stands for the predefined time slot and n stands for a counter

with a limit).

)().......4()3()2()( 3210 nttxtxtxtxtxX n

)().......4()3()2()( 3210 nttytytytytyY n

)().......4()3()2()( 3210 nttztztztztzZ n


A matrix is constructed with the x-y-z axes. Noise suppressor and position predictor

algorithms are used with matrix base mathematical operations to “recover” the real position

from the raw data (typical from the sensing elements inaccuracies) and a 3-dimensional

trajectory diagram.

According to the flight operation plan provided in the HASP website; the platform will launch

at a rate of about 1000 feet per minute. Thus, with this ascent velocity is expected that the

payload reach the float altitude (i.e. 120,000 feet) in approximately 1 ½ to 2 hours. The actual

flight profile for the 2006 HASP flight is shown in Figure 11.

Figure 11 is a comparison between

a HASP flight (blue curve) and the

profile for typical latex, sounding

balloon flight (red curve). The

vehicle will stay at an altitude (i.e.

at the stratosphere) for about 5 to 15

hours before the flight must be

terminated to parachute HASP into

a safe landing zone.

The trajectory expected for the

HASP payload, considering Figure

11, can be divided in two phases:

that of a turbulent launch and that

of a steady and slow dynamic

behavior. Figure 12 illustrates the

payload’s trajectory, when the payload ascends up to 120,000 feet in two approximately 2

hours and when it reaches a near constant altitude for a time greater than 15 hours but no more

than 18 hours.

The first phase data will

be used to determine the

gradient of temperature

in the physical structure

of the payload and the

possible impact it may

have in the performance

of the internal electronic

components and

subsystems.

A typical communication

link for a small satellite,

in LEO (Low Earth

Orbit), with an antenna

beamwidth of 30, a

height of 700 km, and an average speed of 7,500 km/s will need an approximate time of 22

minutes to pass over the ground station communication.

Figure 11: HASP 2006 flight profile

Figure 12: Payload trajectory dynamics


This is justified by

developing the

following analysis. For

an average Earth radius

plus the height of the

satellite of 7,078 km

(6,378 km + 700 km)

and at the speed of

7,500 km/s the linear

displacement in orbit in

1 minute will be of:

In the preceding calculation s stands for a segment of the circumference that the satellite will

travel in one (1) minute. Then, the angle of translation is determined as follows (s is

approximate as a line but it is really a

segment of a circumference):

1000,078,7

000,125sinsin 1

r

s

Then, at the speed of 7,500 km, the satellite

will travel about 1.

Since the downlink antenna beamwidth chosen is about 30 degrees the angle from the

maximum power density center of the mainlobe and the -3 dB (half of power density) is 15.

In order to assure a robust communication link a 20 angle is chosen. Then the needed

minimum accuracy for orientation used will be 10.

The downlink antenna beamwidth

chosen can also be employ to

determine the accuracy of the

position desired for this project. To

define the position’s accuracy two

important cases must be

considered. One is the movement

of a cube sat along its orbit and the

second is the effect of the orbit

decay in the strength of the

downlink communication signal. In

order to define correctly the

accuracy of the position the most

limiting case for the downlink

communication must be examined. This limiting case occurs when the satellite is pointing

Figure 13: Angle of translation determination

min/000,125

min1

60

1

/500,7ms

ssm

Figure 14: Angle of translation determination

Figure 15 Beamwidth shade diameter determination


directly downward, because is in this orientation where the signal covers less distance in

comparison with other types of orientations. If a height of 400 km out of the earth’s

atmosphere is considered for the cubesat’s orbit and a beamwidth of 300, the distance covered

by that situation is of 214 km. The visualization and procedure follow to determine this

distance is shown in the following figure:

Figure 16: Determining position accuracy

This implies that if a 3db of power density don’t want to be lost in the communication link at

least an accuracy of a 100 km should be used for the position. If the effect of orbit decay in

the strength of the downlink communication signal is examined considering that at least 100

km have been lost it’s found that the 214 km of covered distance from the previous case (i.e

400 km of height), have been reduce to approximately 160 km. This means that the second

case suggests a smaller value of position accuracy do to the effect of the cubesat’s orbit decay,

therefore it can be concluded that the lost in altitude will be the limiting factor to establish the

accuracy of the position.

Figure 17: Determining position accuracy with orbit decay

An examination of previous data must be employ to completely define the accuracy of the

position considering the phenomena of orbit decay. That is why data of orbit decay is

retrieved from the Department of Industry Tourism and Resources to complete this task. This

data is illustrated in the following figure:


Figure 18: Plot of typical orbit decay

Figure 18 illustrates that the satellite starts a rapid descend at the time the satellite reaches an

altitude above the earth’s atmosphere of approximately 300 km. Therefore from this plot it

can be inferred that this height will establish the limits of distance covered by the downlink

communication signal which is this case of 160 km. Thus, it can be concluded that in terms of

communication the accuracy required should be at least of 80 km.

As described in the Science Objectives section it is also of interest the behavior of the

temperature as well as the response of the physical metallic enclosure of the payload under the

same temperature changes. The temperature of the atmosphere varies as a function of height

and as a function of the rotational position of the Earth. The temperature gradient can be

obtained when at least two temperature sensors (one inside the payload and the second outside

of its physical structure). The change of temperature from one point to the other presents the

flow of energy (in heat form) from the hotter point to the cooler. This is known as conduction

when it happens between the particle of a material (better in metals where metallic bonding is

stronger) and radiation when it happens through empty space. The temperature gradient will

help determine the influence on the internal components of the payload and as well as

determine the effectiveness or behavior of the external physical structure.

As described in the Science Objectives section it is also of interest the behavior of the

temperature as well as the response of the physical metallic enclosure of the payload under the

same temperature changes. The temperature of the atmosphere varies as a function of height

and as a function of the rotational position of the Earth. The temperature gradient can be

obtained when at least two temperature sensors (one inside the payload and the second outside

of its physical structure). The change of temperature from one point to the other presents the

flow of energy (in heat form) from the hotter point to the cooler. This is known as conduction

when it happens between the particle of a material (better in metals where metallic bonding is

stronger) and radiation when it happens through empty space. The temperature gradient will

help determine the influence on the internal components of the payload and as well as

determine the effectiveness or behavior of the external physical structure.

The temperature changes significantly while it is ascending in the atmosphere. Figure 19

demonstrates the HASP payload during its ascending and floating time as it was exposed to a


very extreme environment that consists of very low and high temperatures at a very low

pressure (i.e. 5 – 10 millibars).

Figure 19 illustrates the lowest

temperature that was found on

the platform’s top was of -80 0C and could be lower due to

the form of the curve. The

highest temperature

encountered during the 2006

HASP flight was of

approximately 40 0C. The

exposure to these

environmental conditions is

what makes necessary the

design of a thermal control

system so that the electronic

equipment inside the payload can be kept working at its optimal temperature range.

The description of the ADS above, including the chosen attitude determination reference

frames are intended for a robust and precise control of satellite for ground station contact. In

order to test the proposed operation of the ADS, the collection of data needs to be done with

adequate technology. The data collected will determine the attitude of the payload within the

abovementioned reference frames. Proper design and programming of hardware components

and sub-systems are intended to record the relevant data that will be post-processed to

determine the tracking of the payload during the whole test flight.

3.3.2 Science Requirements

To accomplish the development of a robust ADS prototype that would be used to determine

the orientation of a satellite, it is necessary to define the requirements that are needed to obtain

the orientation, position and heat characteristics of the payload throughout the flight. These

requirements are:

1. Determine the payload position within accuracy of 80 km.

2. Determine the heat transfer rate into or out of the payload.

3. Verify the orientation of the payload by comparing an external reference magnetic

field and the International Geomagnetic Reference Field (IGRF) model of the year

2010.

4. Use and verify the position accuracy of the Inertial Measurement Unit (IMU) with

respect to the position GPS data.

5. Use the obtained data to gather knowledge about the attitude motion of the payload

and provide recommendations for future HASP and CubeSat projects.

6. Complete final science report post flight.

Figure 19: Temperature variation during flight


3.4 Technical Background and Requirements

3.4.1 Technical Background

The ADS developed in this project consists of several sensors and a data processing unit used

to collect and store the measurements needed to determine the payload’s position and

orientation at intervals of time during the flight. The ADS is use to determine the payload’s

attitude, using different reference frames that will be established by the following equipment:

Accelerometer

For application with space and weight limitations there are three different kinds of

accelerometers commonly used which are the piezoelectric micro-accelerometer,

capacitive micro-accelerometer and the tunneling current micro-accelerometer. The

type of accelerometer selected for this application is the piezoelectric micro-

accelerometer. It has been selected because its measures are not affected by parasitic

capacitance or electromagnetic interference (EMI) which is disadvantages of

capacitive accelerometers. In addition piezoelectric accelerometers don’t require a

high voltage like the tunneling current accelerometer. The piezoelectric accelerometer

selected is an electromechanical device that obtains acceleration using the relation that

exists between a piezoelectric deformation and the rate of change of the velocity in the

body. When the body of the system accelerates a force is created and this force

produce a deformation in the small piezoelectric that form part of the sensor. The

principle of operation of these devices is presented in the following Figure 17.

Figure 20: Accelerometers basic principal of operation

As the body moves the mass in the sensor due to its inertia moves in the vertical

direction producing a deformation in the beam. The piezoelectric is embedded in the

location of the beam’s maximum deflection and is that deformation which affects the

piezoelectric producing a change in the piezoelectric structure. This piezoelectric

deformation causes a change in the piezoelectric resistance that consequently will alter

the output voltage of the piezoelectric of the specific axis where this inertial change

occurs. This amount will permit us to determine the linear acceleration of the payload

during the flight. This device will allow us to understand the payload behavior better,

thus allowing better knowledge of payload’s motion. An average sensitivity of

10mV/g is commonly encountered in this type of sensors.


Gyroscope

The three-axis gyroscope is a device for measuring the payload’s degree of rotation.

The types of gyroscopes commonly used for applications with space limitations are the

Micro Electrical Mechanical System (MEMS) gyro. These types of gyroscopes are

compose by miniature mechanical elements that vibrates and electronic components

used to process the data produced by the mechanical elements. The vibration of the

mechanical element is affected every time the payloads rotate due to the Coriolis effect

(see section #), which produce a vibration in direction different to direction of the

initial vibration. This resultant vibration is directly related to the angular velocity of

the payload’s rotation. This second vibration is sensed and processed by the electronic

equipment in the gyroscope to finally determine the payload’s angular velocity

readings. To illustrate the principal of operation of these devices consider the

following figure:

Figure 21: Gyroscopes basic principal of operation

The gyroscope readings will provide information about the payload’s rotation on each

one of the axes. The gyroscope and accelerometer data can be combined to acquire a

more precise measure of the payload’s orientation.

Three-axis magnetometer

The ADS system of the payload will take measurements of the strength of the Earth’s

magnetic field. These measurements will be used to obtain the position of the payload

during the complete flight. The magnetometer detects the magnitude of the earth’s

magnetic field on each axis, in this case; X, Y and Z. To obtain the magnetic field the

magnetometer works by measuring the magnetic filed through magneto inductance by

using a circuit that is magneto inductive (which consist of a coil around a

ferromagnetic core). A relaxation oscillator connected to this magnetic circuit works

by gradually building up charge in the circuit and discharging rapidly, this cycle

repeats itself. As the strength of the magnetic field varies so does the frequency of

oscillation in the coil that is perpendicular to field. The output of the magnetometer is

in form of a square wave signal that can be read as a digital signal. This output


represents the magnitude of the magnetic field on a specific axis; having three

magnitudes will allow the calculation of the earth magnetic field vector.

Figure 22: Simplified representation of magnetometer basic operations

The magnetic field is directly related to the cosine of the angle; as a result, when the

angle changes, the magnetic field will change will result in a change of voltage at the

output of the sensor. The following equation represents the relationship between the

magnetic field and the angle at different times.

Where and is the magnetic constant field. Note that the output of the

magnetometer is measured in volts depending directly on the strength of the field

along the axis. Three different circuits as described above would be needed if three

dimensional frame detection is desired.

Temperature sensor

Different kinds of temperature sensors have been develop in the present to meet

diverse kind of requirements that can appear in a variety of applications. These sensors

differ in their ranges of measurements, sensitivity, accuracy, and mode of sensing. The

different kinds of temperature sensor that exist today can be classified as

thermocouples, thermistors, RTD’s, or solid state sensors. For this application the

temperature device considered is solid state sensor. An illustration of this type of

sensor is presented in the following figure:

B

B component along coil axis


Figure 23: The DS18B20 Digital temperature sensor

A DS18B20 digital temperature sensor will gather the internal temperature

measurement. The measurement range of the digital temperature sensor is from -55ºC

to +125ºC. Once the temperature reading has been realized, the DS18B20 converts the

temperature into 12-bit digital word. The communication between the microcontroller

and the digital temperature sensor is through 1-wire bus that requires only one data

line (by definition). The data obtained by the DS18B20 will remain when the device is

powered down, since an EEPROM is included in the DS18B20 temperature sensor.

The user can configure the resolution of the temperature sensor.

Figure 24: DS18B20 Digital Temperature Sensor Diagram (From the DS18B20 datasheet)

Figure 21 shows an example to power the DS18B20 temperature sensor that is shown

in the datasheet. An external power supply can be used to power the DS18B20

temperature sensor in the pin. The DS18B20 has the feature of receiving power

from the data line (power supply range is from 3.0V to 5.5V); however, the advantage

of power the DS18B20 by an external power supply is that the MOSFET pullup is not

required, and the 1-Wire bus is free to carry other traffic during the temperature

conversion time.

Sampling rate

The sampling rate is the pace of taking measurements at a specific amount of time.

The selected sampling rate for this project is 10 s and applies for the entire data

acquisition sequence. This rate is necessary to obtain the data needed for orientation


and position within a specific accuracy and, at the same time, to calculate the amount

of storage needed for it. This rate was determined as follows. A video from the HASP

2007 project, where a balloon payload dynamics were recorded, it was observed that

the platform was moving at an approximately maximum angular velocity of 90 in

approximately 90 minutes, that is, 1 degree per second.

For an accuracy of 10,

as determined above for

the communication link

constrain, a minimum

sampling rate of 10

seconds is chosen so the

system knowledge for

proper attitude

determination is

updated for a

maximum of angular

change of that angle.

This 10 accuracy determine also the linear trajectory of the payload when changes its

position to a 55 meters per second. This value is obtained from the fact that the

payload moves approximately 300 km in 15 hours which is equal to 5.55 m/s.

3.4.2 Technical Requirements

The requirements about the technology needed to accomplish them to determine the

orientation, position, and heat characteristics of the payload are:

General:

1. To develop a payload that requires less than 30V at 0.5Amps, provided by HASP, and

as well to meet the CubeSat power requirements.

2. Develop a mechanical structure that can withstand all the stresses during the payload’s

flight.

3. Maintain the internal temperature in the range of -10oC to 60

oC.

4. Obtain the data at a sampling rate of 10 s.

Specific:

1. Employ a three axis accelerometer with an accuracy ± 2% to determine the position of the

payload within 55 meters.

2. Determine the orientation by employing accelerometers with an accuracy of ± 2% and

gyroscope with an accuracy of 0.01o/hr (angular velocity) to develop an Inertial

Navigation System.

3. The rate of heat transfer is to be determined by using a pair of temperature sensor (internal

and external) with a size of no bigger than 4 mm (because of space contraints) and an

accuracy of ± 1 oC.

4. Determine orientation with a 3 axis magnetometer with accuracy of 10o

Figure 25: Determination of sampling rate by maximum angular

velocity


5. Determine position from a three axis accelerometer that has an accuracy of ± 2% and a

reference Global Positioning System sensor.

6. Develop an integrated system of sensor such as magnetometer (10o

accuracy)

accelerometer (± 2% ) and gyroscope (0.01o/hr) at a sample rate of 10s.

4.0 Payload Design

The ADS experiment has a sensor subsystem of five main sensors that will take measurements

to study the balloon platform dynamics. The design arrangement for the experiment consist of

rotational sensor, acceleration sensor, magnetic field sensor, and internal temperature sensor

to acquire data at different positions to get exact information about the Attitude of the

payload.

4.1 Principle of Operation

The ADS experiment will take a variety of measurements, such as acceleration, orientation,

temperature, position, and magnetic field. A three axis accelerometer sensor will be use to

obtain the acceleration data which in the post analysis will be used to obtain velocity and

position and will be compare to the GPS data. The magnetic field concentration will be

determined by a three axis magnetometer to obtain the orientation of the payload. Also the

orientation will be determined by a combination of the gyroscope and accelerometer to obtain

robustness. The internal temperature data will be obtained by an internal temperature sensor

used to monitor the payload’s internal environment to see when the temperature limits of the

devices are reached.

4.2 System Design

Mechanical System

Three Axis

Accelerometer

Flight Control

System

Microcontroller

Three Axis

Gyroscope

Three Axis

Magnetometer

Digital

Temperature

Sensor

Real Time

Clock

SD Card MemoryLegend

Data from Clock

Data from the Sensors

Payload Structure

Transmission of

Data

Figure 26: ADS System Design


The system design (Figure 23) shows the elements of the ADS system. The clear blue

connections designate the data exchange between the flight control and the sensors that will

be in the payload. The green line represents communication between the Microcontroller and

the Real Time Clock to obtain time and day data. The data obtained from the sensors will be

saved in the SD card; this communication is represented by the red line. The light gray line

and the mechanical system box represent the ADS payload structure. The temperature sensor

box represents the internal temperature sensor. The power subsystem is explained in more

detail in the sections 4.3.4 power supply and 4.3.5 power budget.

Arduino Pro 328

An Arduino Pro 328 version 3.3V/8MHz

will be used as the flight control computer

for the ADS experiment. Figure 4 shows

328 provides 3.3V and 40 mA on each of

the I/O pins. The clock speed for the 3.3V

version is 8 MHz. The has both SPI and

I2C interface; as a result sensors with SPI

and I2C protocol can communicate with

the Pro 328. As mentioned above, the

accelerometer and the magnetometer

sensors have SPI interface. Both sensors

have a unique pin for their slave select;

therefore, the Pro 328 can send the

instruction via the developed program to

the sensor that is assigned to read once

the data is available. The gyroscope

sensor can communicate with the Pro 328 using the I2C protocol.

SCA-3000-D01

The schematic for the SCA-3000D01 three axis

accelerometer sensor is shown in Figure 28. The SCA-

3000-D01 has a measurement range of + 2g and has an

SPI digital interface. The SEN-08791 Breakout board

includes an SCA3000 and provides 8 pins in this board.

The pins are as follows; VIN, RST, INT, MOSI,

MISO, SCK, CSB and GND. As mentioned in previous

section 4.4.2 Flight Software, for SPI interface the data

transfer consist of a 4 wire interface; MOSI, MISO,

SCK and CSB. The MOSI and MISO pins stand for

master out slave in and master in slave out

respectively. In addition, the SCK stand for serial clock

and is used to synchronize all the devices. Finally, in

order to select this sensor to communicate with the microcontroller instead of the other slaves,

the SCA-3000-D01 includes a CSB chip select that will be activated by the Pro 328

microcontroller when the Pro 328 sends a signal through this pin. The CSB pin is low active.

Figure 27: Arduino Pro 328 3.3V/8MHz schematic

Figure 28: Three Axis Accelerometer

schematic


MicroMag3

Figure 29 shows the schematic for the MicroMag3 three

axis magnetometer. The MicroMag3 provides a

measurement range of +1100µT ( +11 Gauss). The

MicroMag3 has a total of 14 pins; however, from pin 8 to

11 and pin 13 are not connected pins. Therefore, the pins

that will be used are 1 through 7, 12 and 14. The functions

of these pins are SCLK, MISO, MOSI, SS, DRDY, RESET,

GND, VDD and GND respectively. The MicroMag3 has an

SPI digital interface; therefore, the pins MISO, MOSI,

SCLK and SS are SPI pins. SCLK and SS pins are the serial

clock and the slave select respectively. The RESET pin is

usually low and can be used by the Pro 328 during the

program testing to reset the sensor and run the program. The

DRDY stand for data ready and is recommended that once the data is available it is clocked

out of the MicroMag3; however, this pin is not used since the sampling rate for the ADS

experiment will be different from the rates mentioned in the MicroMag3 datasheet.

Three Axis Gyroscope

The ITG-3200 is a three axis gyroscope, it consist of

seven; these pins are VCC, SCL, SDA, VLO, INT,

CLK and GND. Both the INT and CLK are not used

these are an interrupt pin and a pin for an external

clock, CLK needs to be grounded if it is not used. In

Figure pin 6 and 7 are I2C these pin are connected to

the digital pins on the Pro 328, these pins require

pull up resistors to VDD. The VLO in generally it is

connected to the pin 1. Notice that C1 and C2 are

used as decoupling capacitors to allow a clearer

signal.

Digital Temperature Sensor

The DS18D20 is a one wire

digital thermometer with 3 pins

in a TO92 package, the pins are

GND, VDD and DQ. In Figure

it is illustrated that pin 2 needs a

pull-up resistor of 4.7kΩ. Pin 3

is supplied with 3.3V with a

series capacitor to reduce noise. This sensor is connected to digital pin 13 in the Pro 328.

Figure 29: Three Axis

Magnetometer schematic

Figure 30: Three Axis Gyroscope schematic

Figure 31: Digital Temperature Sensor schematic


Micro SD Transflash

CD: Card detect

DO: Data output

GND: Ground

SCK: Clock

VCC: Supply Voltage

DI: Data Input

CS: Chip Select

In Figure 32 is demonstrated the Schematic of the SD

Card transflash board with the connections to the

microcontroller. This device has 7 pins CD, DO, GND,

SCK, VCC DI and CS. The serial peripheral interface

(SPI) pins are DI, DO, SCK and CS. As with previous

sensors the capacitor C6 will reduce noise and allow a

clearer signal. Pin 7 is not used when using SPI mode,

pin 7 is mostly used in SD mode.

Serial Alarm Real Time Clock (RTC)

Figure 33 demonstrates the

schematic and pin configuration

use for this experiment. This RTC

is a DS1306 and it is use to obtain

a time stamp. The pins used will

allow to obtain the time without

using any alarm features. Pins 3

and 4 are use for the crystal; the

recommended crystal is a

32.768kHz Quartz crystal with a

series resistance of 45kΩ and a

capacitance of 6pF. Pin 10

through 13 are use for SPI. Pin

16, 14 and 9 needs to be connected to the source, the capacitor C7 allows a clear input signal.

A lithium 3V cell is used as a backup battery in pin 2. In this configuration Vcc2 is connected

to pin 8 and GND. This device is connected to the digital pins in the Pro 328 for SPI.

9V DC to DC

Converter

Connected to the 9V

DC to DC converter

is the power

supplied by HASP

which is 30V @

500mA as shown in

Figure: through

pins 1 and 2. A 3A

diode is used to

Figure 32: MicroSD board schematic

Figure 33: Real-Time Clock schematic

Figure 34: 9V DC to DC Converter schematic


avoid any damage to the devices if a wrong connection is done. The C8 through C11 and C14

is to reduce noise and to guarantee the full parametric performance over the full line and load

range. The 9V output will supply the Pro 328 and the Linear Voltage Regulator. This device

has an efficiency of 80%.

Linear Voltage Regulators

Each one of the sensor and the SD card memory that will

be used for the ADS experiment will be powered by

3.3V. The ADS instruments will receive power from the

HASP platform, which deliver 30V at 0.5 Amps. A 9V

DC to DC converter will transform the 30V provided by

the platform into 9V to power the Pro 328. Since the ADS

electronics (with the exception of the Pro 328 and the DC

to DC converter) will be powered by 3.3V, an

UA78M33IKCS 3.3V linear voltage regulator is required

to reduce the 9V delivered by the DC to DC converter.

The 3.3V linear voltage regulator will remove the excess voltage and it will turn it into heat to

provide the 3.3V.

This device is a linear voltage regulator capable of providing 5V

output for the Real Time Clock since it requires that the input

voltage be higher than 3.2, the device did not work with a input

voltage of 3.3V. The power of the regulator is obtained from the

9V DC to DC converter.

4.2.1 Functional Components

1. Power Subsystem: 0.5 Amps @ 30 VDC will be provided by the HASP platform

during the entire flight. A power budget analysis is required to ensure that this power

will be sufficient for the instruments of the ADS experiment for the entire period of

flight.

2. Microcontroller: The Arduino Pro 328 microcontroller, which is connected to all the

instruments, is in charge of collecting the measurements from all the sensors and stores

it to the memory.

3. SD Card Memory: The SD card memory module will be added to the Arduino were

the measurements of the sensors will be stored here as digital quantities.

4. Three Axes Accelerometer: The accelerometer will take the acceleration

measurements of the payload. Each one of it axes will perform measurements related to

the payload response on that axis.

5. Three Axes Gyroscope: The gyroscope is in charge to determine the orientation of the

ADS payload by sensing the platform rotation during flight.

6. Three Axes Magnetometer: The magnetometer will measure the earth’s magnetic field

intensity.

7. Internal Temperature Sensor: The internal temperature will be monitored by the

flight control computer using an internal temperature sensor. The internal temperature

Figure 35: 3.3V Voltage Regulator

schematic

Figure 36: 5V Voltage

Regulator schematic


readings will be compared with a particular temperature value set in the program of the

microcontroller to identify at what time the maximum temperature is reached.

8. GPS Data: Will provide the position and altitude information of the platform obtained

through HASP website.

9. Mechanical System: The mechanical system is the enclosure of the subsystem

components for the experiment. An aluminum 2014-T4 alloy will be use to construct the

mechanical system to isolate the circuit components and protect them from the

temperature.

10. Thermal Subsystem: The main purpose of the thermal system is to maintain the

internal temperature of the payload within the operating temperature range of the sensors

and the components at the same time protect them from any impact that can damage it.

11. Data Gathering and Analysis: The Pro 328 has to execute the flight software to

gather the sensors measurements and stored it in the SD card. Once the data is extracted

from the SD card several plots will be made to analyze the data and develop new

recommendations.

12. 9V DC to DC Converter: The purpose of this device is to transform the high level

voltage of 30V to 9V to supply the Pro 328 and the linear regulator.

13. 3.3V Linear Voltage Regulator: To supply the sensor with the voltage level of 3.3V it

necessary to use the regulator do to it efficiency with low voltages.

14. 5V Linear Voltage Regulator: To supply the real time clock with the voltage level of

5V it is necessary to use this regulator.

4.2.2 Component Interfaces

The Attitude Determination System will be composed of the following interfaces. The Pro

328 is going to be connected with each one of the sensors output which are digital pins its

interface will be composed of the necessary traces on the PCB. The power subsystem will

have connection with the sensors subsystem and with the Pro 328 to deliver power to both

subsystems, thus permitting for each sensor to receive the power necessary to operate within

the specifications by the use of a 9V DC to DC converter and 3.3V Linear Voltage Regulator.

Also decoupling capacitors will be use to allow a power clearer signal by reducing noise from

the power system. In sections 4.3.3 to 4.3.5 is an explanation in greater detail of the power

interfaces and consumption. The interface between the Magnetometer, Accelerometer and

Gyroscope is a direct connection to the digital pins of the Pro 328. A direct connection

interface with the SD card memory module is used to receive the information that will be

stored. To store the data in micro SD card it is necessary to use a time reference, having the

need for a RTC and its interface is a SPI trace throughout the board.


4.2.3 Traceability

Table 1 below shows the traceability matrix for the ADS experiment.

Main Mission Goal Objectives Requirements Implementation

The goal of this project

is to develop an attitude

determination systems

(ADS) prototype, by

improving the

robustness and

accuracy of a previous

design (ABITA; Tiger

team) in order to obtain

relevant data and

hands-on experience for

a future satellite

attitude control and

determination system

(ADCS). The

designing, developing

and testing will serve as

a stepping stone for a

future CubeSat project

with the objective to

transmit to a ground

station the

measurement data that

has been applied for the

terrestrial gamma ray

flashes (TGF).

Previous CubeSat data

will help as a basepoint

for this design.

To determine

translation and

attitude motion of

the payload during

flight

Determine the

payload position

within accuracy of 10

meters.

Combining the

acceleration and

movements in pitch,

yaw and roll data

from the

accelerometer and

gyroscope

To obtain the

platform’s body

frame orientation

with respect to the

body fixed

reference frame

Determine the

acceleration with an

accuracy of ± 2% and the angular velocity with an accuracy of

0.01o/hr

Employing an

accelerometer with

a resolution of

0.002g and a

gyroscope with a

sensitivity of

14.375 LSB/dps

To measure the

Earth’s

gravitational and

magnetic field and

the angular

momentum of the

payload such that

the data can be

used to determine

the orientation of

the payload.

Determine the

magnetic field with an

accuracy of 10o

Develop an

integrated system

with a

magnetometer with

a resolution of

15nT

Determine the

gravitational field

with an accuracy of ± 2%

Develop an

integrated system

with an

accelerometer with

a resolution of

0.002g

Determine the angular

momentum with an

accuracy of 0.01o/hr

Develop an

integrated system

with a gyroscope

with a sensitivity

of 14.375 LSB/dps

Determine the heat

transfer

characteristic

during flight and

its potential impact

on internal and

structural

components.

Determine the

temperature in the

range of -10 to 60oC

and a accuracy of

0.5%

Use a small signal

diode that can

operate from -30 to

-90oC

Table 1: Traceability Matrix


4.3 Electrical Design

Sensors Subsystem

3-Axis

Gyroscope

3-Axis

Accelerometer

3-Axis

MagnetometerInternal

Temperature

Flight Control Subsystem

Atmega 1280 Arduino

SD Card

Memory

Digital

Inputs

Digital

Outputs

Legend

Sensors Digital Outputs

HASP0.5 Amps @ 30 VDC

Power

Real Time

Clock

Figure 37: Electrical Design Subsystems

As shown in Figure 37 the electrical design consists of three main subsystems; the power

subsystem (HASP), the flight control subsystem and the sensor subsystem. The power

subsystem consists of the power provided by HASP, the DC to DC converter and the linear

voltage regulator. The sensor subsystem is composed of digital devices; therefore these signal

outputs from the sensors will be received by the Pro 328 as shown in Figure 37. The flight

control subsystem will gather data from all instruments. The sensors subsystem consists of

four sensors; a three axis accelerometer, a three axis gyroscope, a three axis magnetometer,

and an internal temperature sensor.

4.3.1 Sensors Subsystem

Sensors Subsystem

3-Axis

Gyroscope

3-Axis

Accelerometer

3-Axis

Magnetometer

Internal

Temperature

Flight Control Subsystem

Arduino Pro 328

Digital

Inputs

Digital

Outputs

Legend

Sensors Digital Outputs

Analog

Inputs

Analog

Outputs

Figure 38: Electrical Subsystem


The electrical subsystem is shown in Figure 38 above which allows observing a general view

of how the electrical connections will be done. The sensor subsystem is represented in the left

box and Pro 328 is represented by the right box. The interface between the Pro 328 and each

one of the sensors is represented with the lines with ends. The line ends points at the direction

that the information will be flowing, which is from the sensors to the Pro 328 through the SPI

pins for Magnetometer and the Accelerometer, I2C for the Gyroscope and a digital pins for the

Internal Temperature sensor.

The SCA3000 is a digital three axis accelerometer with an acceleration range of +2 g. The

digital I/O voltage of the SCA3000 is from 1.7 V up to 3.6 V. The digital outputs range of the

SCA3000 accelerometer is from 2.35 V up to 3.6 V.

The sensing element of the SCA3000 three axis

accelerometer consists of three acceleration sensitive masses.

A capacitance change will occur due to acceleration and will

be converted into a voltage change in the signal conditioning

ASIC. The element’s measurement coordinates are rotated

45º compared to the conventional orthogonal X, Y, Z

coordinate system, due to its mechanical construction.

The sensing element is interfaced via a capacitance-to-

voltage (CV) converter. The SCA3000 includes an internal

oscillator, reference and non-volatile memory that enable the sensor’s autonomous operation

within a system. The SCA3000 includes a temperature sensor; therefore, temperature stability

can be reached by using the temperature information from this sensor.

The Figure 40 shows the pins for the SCA3000.

The accelerometer can receive instructions from

the Arduino microcontroller by connecting an

output pin to the accelerometer Master Output

Slave Input (MOSI) pin. The Pro 328 represents

the Master and the accelerometer the slave.

The SCA3000 can be set to operate at low power

to save system level power consumption by using

the Motion Detection (MD) mode. When the Free-

Fall Detection (FFD) is enabled normal

acceleration is available.

The EQUIS team selected the ITG-3200 three axis gyroscope for the ADS experiment. As

mentioned in previous sections, the ITG-3200 is a three axis gyroscope with digital outputs.

The full scale range of the ITG-3200 three axis gyroscope is + 2000 º/s. The ITG-3200 has

digital (I2C) outputs. The operating voltage range of the gyroscope is from 2.1 V up to 3.6 V.

Figure 39: Accelerometer Sensor

Figure 40: SCA3000 Three axis accelerometer

pins


The pins to receive the digital instructions are shown in Figure 29. The ITG-3200 is a three

independent vibratory Micro-electro-mechanical System (MEMs) gyroscope sensitive to

Coriolis forces. The ITG-3200 can detect rotational rate in three axis; the X (roll), Y (pitch),

and Z (yaw).

A rotation about any of the sense axes of the gyro must be induced to create a Coriolis Effect,

which causes a deflection that is detected by a capacitive pickoff. The MEMs device applies

the following process to the detected signal; amplification, demodulation and filtering that

produce a voltage that is digitalized with an internal ADC. The converted voltage is

proportional to the angular rate. The ADC output rate is capable from 3.8 up to a maximum

8,000 sample per seconds, while allowing a wide range of cut off frequencies due to its

capability of a user selectable pass filter.

A MicroMag3 three axis magnetometer has been

selected for the earth’s magnetic field measurements of

the ADS experiment. The three axis magnetometer

sensor operates as an oscillator circuit composed of the

internal sensors, bias, resistors, digital gates and a

comparator. Only one sensor can be measured at the

time. The user sends a command byte to the MicroMag3

through the SPI port specifying the sensor axis to be

measured. A model of the MicroMag3 is shown in

Figure 42.

The micromag3 three axis magnetometer has a low power: draws < 500 µA at 3 VDC and

have a field measurement range (3 VDC at Rb = 43Ω) of +1100 µT. The micromag3 has a

fully digital interface: SPI protocol at 3V, it can also be powered at 3.3V.

A DS18B20 will be the internal temperature sensor for the ADS

experiment. The master (the Pro 328) must issue a convert T

[44h] command in order to initiate a temperature measurement.

The DS18B20 stores the temperature measurement in the 2-byte

temperature register in the scratchpad memory, and then the

DS18B20 will return to its idle state.

Figure 41: Gyroscope Sensor

Figure 42: Three Axis Magnetometer

Figure 43: Digital Temperature

Sensor


The time during flight will be provided by the circuit of an

RTC-Real Time Clock shown in Figure 44. The specific model

will be the DS1306, which can withstand a temperature range

of -40ºC to 85ºC. This device is reliable due to the fact that it

allows to have a backup battery, which in this experiment it

will be a +3V Lithium battery additional to the constant source,

which is 5V. In addition, this device requires a crystal of

32.768 kHz, 6 pF and a resistance of 45 kΩ.

4.3.2 Sensor Interfacing

The sensor connections with the Arduino are as shows the following table;

Sensors Sensors Pins Arduino Pro Pins

Gyroscope (I2C) SCL A4

(I2C) SDA A5

Accelerometer RST 2

SS ACC 3

Magnetometer SS MAG 4

DRDY MAG 5

RESET MAG 6

Digital Temp DQ 7

SD Card SS SD 8

Real Time Clock SS RTC 9

Accelerometer Magnetometer

(SPI) MOSI 10

(SPI) MISO 11

(SPI) SCK 12

Not Connected TBA 13

Not Connected TBA 14

Table 2: Pins for the Pro 328

All the sensors will have an interface between each one of the outputs and the Pro 328. All the

sensors for the ADS experiment are digital sensors; therefore, they do not require any

additional components besides a decoupling capacitor to allow a clearer signal.

Figure 44: Real Time Clock


Figure 45: ADS PCB Design

Figure 45 shows the Print Circuit Board (PCB) design for the ADS experiment. Each one of

the components is represented with yellow lines with its actual size and the corresponding

name. The holes that are required for the PCB to place the components and connect traces

were also realized using the actual size of the leads of each component and are represented

with red circles.

The complete schematic design was linked to the PCB design to enable a tool of the Express

PCB software that indicates the pins that need to be connected according to the schematic.

Several traces were designed on the PCB to realize the required connection between the

components. The green and red lines represent the traces that connect the components in the

PCB. The red lines are the connection traces designed in the top copper layer and the green

lines are the connection traces in the bottom copper layer. When a trace is made in both

copper layers (top and bottom) to make a connection between two components, pass through a

hole to allow connection. Finally, the yellow square that surrounds all the components, holes

and traces represent the actual dimension of the PCB, which is 4 x 4 inches.


4.3.4 Power Supply

30V

3.3V

3.3V9V

5V

3.3V

3.3V

3.3V

30V

9V

HASP

0.5 Amps

at 30 VDC

FUSE Box

9V DC to DC

Converter

Three Axis

Magnetometer

Three Axis

Accelerometer

Three Axis

Gyroscope

Arduino Pro 328

SD Card

Real Time Clock

Digital Internal

Temperature

Sensor

3.3V Linear

Voltage

Regulator

5V Linear

Voltage

Regulator

Figure 46: Power System Diagram

The power subsystem for the ADS experiment is shown in Figure 46. The HASP platform

will be the power source for the ADS experiment and will deliver 30V at 0.5 Amps to the

ADS payload. The fuse shown in the figure 33 is included in the power subsystem to isolate

the ADS electronics from the HASP platform as a safety precaution. As mentioned in the

section 4.2 System Design, a 9V DC to DC Converter will transform the power from the

platform to power the Pro 328. Also a suitable supply of 3.3V is being delivered through a

Linear Voltage Regulator that is represented in the Figure 33 to power the Micro SD board

and all the sensors. Also a 5V voltage converter is used to supply the 5V required for the

RTC.

The Pro 328 has an input voltage range from 3.35V to 12 V; however, the voltage regulator of

the Pro 328 Board may overheat and damage the board when is using more than 12 V and if

the supplied voltage is less than 7 V, the 5 V pin may supply less voltages on the pins and the

board may be unstable [Ref. 14]. Therefore, the Pro 328 will receive 9 V from a DC to DC

converter as shown in Figure 46.


4.3.5 Power Budget

The HASP- High Altitude Student Platform provides power for small and large payloads. For

small payloads the supplied voltage that HASP platform provides is 0.5 Amps @ 30 VDC.

Sensor and Devices Required Voltage

(V)

Required Current

Amperes (A)

Power Consumption

Watts (W)

Power Source

(after HASP) Three Axis Gyroscope

ITG3200 3.3 6.5mA 21.45mW

3.3V Linear

Regulator

Three Axis Accelerometer

SCA3000 3.3 .650uA 21.45uW

3.3V Linear

Regulator

Three Axis Magnetometer

Micromag3 3.3 .500uA 1.65uW

3.3V Linear

Regulator

Digital Temperature Sensor

DS18B20 3.3 1.5mA 4.95mW

3.3V Linear

Regulator

Arduino Pro 328 9 200mA 1800mW 9V DC to DC

Converter

Real Time Clock DS1306 5V 1.28mA 6.4mW 5V Linear

Regulator

SD card circuit 3.3 100mA(max)

40-60mA(Typical) 330mW

3.3V Linear

Regulator

Max consumption of sensors

and devices -- 2162mW --

Table 3: Power Requirements

Table 3 demonstrates the current, voltage required, power source and power consumption for

each of the electronic sensors without the power devices as the linear Regulator and DC to DC

converter. Note that the current consumed by the SD card is a maximum value and that the

typical value is in the range of 40mA to 60mA depending on brands.

The total power consumption was obtained through a mathematical analysis that can be

observe in Figure 47, first all the current of the sensors is sum, then multiplied by the voltage

supplied to obtain the power. This current consumed by the sensor is also consumed by the

linear voltage regulator; to obtain the power dissipated by the regulators, the current

consumed is multiplied by the voltage drop of 5.7V in the 3.3V regulator, and this procedure

is also done with the 5V regulator. The 108mA consumed by the 3.3V regulator, the 1.28mA

consumed by the 5V regulator and the 200mA of the Pro 328 are added to obtain the total

current consumed before the 9V converter; this is defined by Kirchhoff Current Law. This

current of 309mA and the voltage of 9V are used to obtain the power consumed which is

2783.5mW. The DC to DC converter need to supply what is required for the components to

work, the converter has an efficiency of 80%. To obtain the total power consumption of the

value power is divided by the efficiency (0.80) thus obtaining the consumption of the ADS

system which is 3479mW. This power value is divided by the 30V supplied by HASP, thus

obtaining the total current and power consumption. The difference between the powers before

and after of the converter will provide the power dissipation of the device. To verify that the


calculation is correct that total power consumption must be equal to sum of the individual

power consumption of all the devices in the ADS system. Therefore:

Total Power = DC to DC Power + Pro328 Power + Regulator Power + Sensor and Devices Power

3479mW 696mW+ 1800mW+ 615.6mW+ 356.4mW+5.12mW+6.4mW

3.3V Linear

Voltage Regulator

Arduino Pro 328

DC to DC

Converter

80% efficiency

9V 200 mA

1800mW

9V

309.28mA

2783.5mW

Sensors and

Devices

200 mA

696 mW

30V 116mA

3479mWHASP Power

30V @ 500mA

5V Linear Voltage

RegulatorReal Time Clock

3.3V 108mA

356.4mW

5V 1.28mA

6.4mW

108 mA

1.28 mA

5.12 mW

615.6mW

Figure 47: Power Budget Analysis

4.4 Software Design

The data will be retrieved from the sensors and thus the software will be designed to store the

data in the SD card.

4.4.1 Data Format & Storage

The total bytes required for the flight is determined by the quantity of the sensors and the total

bytes of the measurement of the sensor times the hours the payload may remain in flight.

The system has four sensors; three axis magnetometer, three axis gyroscope, three axis

accelerometer, and one for the internal temperature sensor. Each sensor with three axes will

have a total of six bytes and the internal temperature sensor will have a total of two bytes. The

time stamp consists of four bytes, one byte for the hours, one byte for the minutes, one byte

for the seconds, and one byte for the date. In total we have 24 bytes for the whole system. The

sample rate will be of approximately 3 seconds. The data will be received 20 times each

minute. The total bytes for the whole flight will be of about 576,000 bytes.


The total bytes required for the system are:

Byte Description

1-4 Time Stamp

5-6 Accelerometer: X axis

7-8 Accelerometer: Y axis

9-10 Accelerometer: Z axis

11-12 Gyroscope: X axis

13-14 Gyroscope: Y axis

15-16 Gyroscope: Z axis

17-18 Magnetometer: X axis

19-20 Magnetometer: Y axis

21-22 Magnetometer: Z axis

23-24 Internal Temperature Sensor Table 4: Bytes Description

The data will be saved in the SD card. The SD card will be formatted FAT 16 before use. The

program will use the SDFat library to create an object to access Fat16 files in SD cards. The

data will be saved as a comma separated values (CSV) format.

4.4.2 Flight Software

To run the code on the Arduino, the code must have two main functions:

Void setup()

o Will run once, when the Arduino starts

o The pins are set (input or output)

Void loop()

o Is an infinite loop, starts running when setup function finishes

o Runs the rest of the code

The magnetometer, accelerometer, SD card, and the real-time clock use the serial peripheral

interface (SPI) to communicate with the microcontroller. SPI is a synchronous serial

communication with one microcontroller (master) and several devices (slaves). The master

provides the clock signal and activates which device (slave) to receive data from. The SPI

uses 4 lines, the slave select line to activate the device, the serial clock line to synchronize the

data communication, the master-in-slave-out (MISO) line to send data from the slave to the

master, and the master-out-slave-in (MOSI) line to send data from the master to the device.

The SPI communication uses the Atmega’s SPI internal registers. The following are the

registers that will be used:

SPDR - SPI data register

SPCR – SPI control register

SPSR – SPI status register

SPIF – SPI interrupt flag


The control register (SPCR) has 8 bits, each bit is a command.

Bit 7 Bit 6 Bit 5 Bit 4 Bit 3 Bit 2 Bit 1 Bit 0

SPIE SPE DORD MSTR CPOL CPHA SPR1 SPR0

Enables

interrupts

Enables

SPI

If bit = 1

sends

LSB

first, if

bit = 0

sends

MSB

first

If bit = 1

sets

master

mode, if

bit = 0

sets slave

mode

Sets

clock

polarity

Sets

clock

phase

Sets SPI

speed

Sets SPI

speed

Table 5: SPCR bit specification

EQUIS software uses SPI mode 0 for the accelerometer and for the SD card and mode 1 for

the real-time clock. In mode 0 the CPOL and CPHA are set as 0; therefore, the leading edge

of the clock uses a sample on the rising edge (signal low to high) and the trailing edge of the

clock uses a setup on the falling edge (signal high to low) of the clock. The SPR1 and SPR0

are set to 1, this sets the clock frequency to 62.5 KHz, because the oscillator frequency is

divided by 128 and the ArduinoPro 328 (3.3v) is of 8MHz. The real-time clock operates on

SPI mode 1 where CPHA is set to 1 and CPOL is set to 0, this makes the leading edge of the

clock use a setup on the rising edge (signal low to high) and the trailing edge of the clock

sample on the falling edge (signal high to low). The SPR1 and SPR 0 are set to 0 setting the

clock frequency to 2MHz. The magnetometer uses another method, bit-banging, instead of

setting the SPCR. Bit-banging uses software to transmit bits (high and low), the magnetometer

recognizes the bits as commands.

The pre-flight software sets the RTC by sending the seconds, minutes, hours, day, and date,

month, and year to the corresponding RTC’s internal registers (code on Appendix C). During

flight the software will read from the RTC’s internal registers to receive the timestamp. Table

6 illustrates the RTC’s registers that will be used to determine their addresses to read data

from and write data to.

Table 6: RTC registers and address map


The software contains a function called spi_transfer it is used to start the transmission. Sets

the data sent to the data transmission register, waits for transmission to complete, and returns

the data from the data transmission register. For example, when reading from the RTC

register, the registers address is sent first to the spi_transfer, so that the RTC can prepare the

register, followed by 0 and the device will send the registers value.

The magnetic field will be measured using a magnetometer, a MicroMag3. The MicroMag3

data sheet suggests following these steps to communicate with magnetometer:

1. Slave select is brought low.

2. Reset the MicroMag3 before each measurement. Reset must be toggled from low-

high-low.

3. Data is clocked in on the MOSI line. Once eight bits are read in, the MicroMag3 will

execute the command.

4. The MicroMag3 will make the measurement.

5. At the end of the measurement, the data ready line is set to high indicating that the

data is ready.

As stated in the MicroMag3 data sheet, the axes are chosen by setting the appropriate bits in

the 0 and 1 bit position in the commanding byte as shown on Table 7. The pseudo code for

the MicroMag3 is shown on Appendix C.

Function BIT 1 (from the commanding

byte)

BIT 0 (from the commanding

byte)

X axis 0 1

Y axis 1 0

Z axis 1 1 Table 7: Axis Select

The accelerometer that will be used in the ADS experiment is the SCA 3000-D01. The

readings for each axis are divided into two registers, most significant byte (MSB) and the least

significant byte (LSB) as shown on Table 8. The data has a total of two bytes.

Table 8: SCA3000 registers

The register is shifted 2 bits to the left making the last 2 bits 0’s thus indicating the registers

are being read. The data consists of the MSB and the LSB by shifting the MSB to the upper 8

bits and using bitwise OR to check which bits are 1’s and the LSB is computed by using a

bitwise AND with F8 hex (11111000b) then the result will be divided by 8. The pseudo code

for the SCA3000-D01 is shown on Appendix C.

The gyroscope (ITG 3200) uses I2C to communicate with the microcontroller using two lines

the serial data line (SDA) and the serial clock (SCK). The commands from the microcontroller


and the data sent use the same line, SDA. The Arduino has a library called “Wire” to setup the

communication with I2C devices.

The software will use the following Wire library functions:

Wire.begin() – initializes the I2C communication (SDA and SCK lines) as a “master”

Wire.beginTransmission(device address) – selects the device and starts the

communication with the selected device from the bus

Wire.send(value) – sends a value to the device, can be a register number or the data if

the register will be written

Wire.endTransmission() – ends the communication with the device, deselects the

device

Wire.requestFrom(device address, quantity) – requests the quantity of bytes that will

be received from the device

Wire.available() – determines if the requested bytes are available to be read

Wire.receive() – the master receives the data from the device and stores it on the

variable, e.g. data = Wire.receive();

The temperature will be measured using a One-Wire digital thermometer (DS18B20). One-

Wire is how the device communicates with the master, using one wire for data and power.

The master sends pulses to the bus to receive the device address; the address is used to choose

the device when multiple one-wire devices are connected on the same bus. Following the

address, the microcontroller sends the register for the command for the device. Two of the

commands that will be given to the DS18B20 are the convert T, this command converts the

temperature and stores the data in the scratchpad memory, and the read scratchpad, transfer

the data from the scratchpad memory to the microcontroller.

The DS18B20 has a default resolution of 12 bits and an increment of 0.0625oC. The program

calculates the temperature by adding first byte (LSB) and the second byte (MSB). The total of

both bytes is checked if the MSB bit has the value of 1 by using the bitwise AND with a

WORD (16 bits). If the total is negative the total will be computed as two’s complement by

XORing the total with a WORD of values all 1 (FFFFh) and adding 1 to the result; the result

is used twice, it will be multiplied by 6 and it will be added with the result of the

multiplication, and then divided by 4. The value is given as an integer, and to separate the

integer with the fraction is calculated by dividing the total with 100 (integer) and using MOD

(modulus) to have the residual of the division.

The SDFat library has three classes:

Sd2Card – has raw access to SD flash memory cards, some of its functions are:

o errorCode() – returns the error code if any error was triggered

o errorData() – returns the data error

o init() – initializes an SD flash memory card

SdVolume – has access to Fat16 and Fat32 volumes on SD cards, some of its

functions are:

o init() - initializes the SD card’s Fat volume

SdFile – has access to Fat 16 and Fat 32 files on an SD card, some of its functions

are:

o openRoot() – opens a volume’s root directory

o print() (used like the Arduino’s print) – prints the data to the file

o open() – opens a file or directory by the file name


o isOpen() – indicates if the file can be created or not

o writeError() – indicates if there were errors writing to the file

o sync() – causes modified data to be written to the SD card

A file will be created at start-up and when the file closes the software will create a new file.

The file names will be EQUIS in addition to three numbers from 000-999, with each file

creation the numbers will increment, e.g. “EQUIS000”, “EQUIS001”, and so on. The pseudo

code for the SD card is shown on Appendix C.

The flowchart explained briefly (complete code on Appendix C):

INPUT

Receive time stamp

Receive data from sensors

Magnetometer

Gyroscope

Accelerometer

Internal temperature

OUTPUT

Save to SD card

Figure 48: Flight software control flow chart


4.5 Thermal Design

In order to maintain the electronic components inside the payload in their operative optimal

temperature ranges and to reduce any measure errors (i.e. bias) that could appear due to

temperature changes, a thermal control system will be adapted inside the payload. During this

experiment the payload will be submitted mostly to the stratosphere thermal environment.

This environment can reach temperature as low as -80 °C and as high as 900C and winds that

fluctuate between 20mph to 100mph. These are the atmospheric conditions that would lead to

drastic changes in the environment surrounding the equipment, producing damage in these

devices. The thermal operating ranges of the main components inside the payload are

presented in the following table:

Electronic equipment

Arduino Gyroscope Accelerometer Magnetometer Digital Temp.

Sensor

Real Time

Clock

-40 to 85(0C) -40 to 85(

0C) -40 to 85(

0C) -20 to 70(

0C) -55 to125(

0C) -40 to

85(0C)

Table 9: Electronic temperature limits

The table illustrates that the device that will limit the temperature parameter inside the

payload is the magnetometer. Considering the temperature range of the magnetometer, a

temperature of 100C is selected as the lowest temperature allowed for the medium inside the

payload.

An evaluation of the overall thermal dissipation from the inside to the external environment

was made to have an idea of the amount of thermal energy that is lost in the payload used for

this application. The worst case scenario was considered in the analysis and the structure is

study at 100,000ft above sea level. In addition is important to mention that the materials and

their dimensions were determined before the analysis.

This analysis was performed considering steady state conditions (i.e. no change at a point with

time) and the coldest environment that the equipment can experience. The assumption of

steady state conditions helps to solve the heat transfer problem without involving any

differential equations or temperature distribution and permits the use of the thermal resistance

concept. The concept of thermal resistance is used mainly for the case of steady heat

conduction through walls or any solid material. Thermal resistances for the analysis of

convection and radiation had been developed considering Newton’s law of cooling and the

Stefan-Boltzmann law, and the expressions obtained can be applied only at the boundary of

the solid material where conduction occurs. The expressions that define the thermal

resistances of the different heat transfer mechanism are the following:

Conduction: Convection: Radiation:

Rcond = L/kAs Rconv =1/hconvAs Rrad=1/hradAs

To simplify even more the heat transfer analysis performed the overall heat transfer

coefficient term is used so that the heat loss by the inner space can be expressed using only

one expression instead of considering each heat transfer mechanism separately. This

expression is analogous to Newton’s law of cooling and has the following form:


Q=UA∆T

where:

U = overall heat transfer coefficient

UA = 1/Rtotal

Is important to mention that convection was examined in this analysis so that all the possible

heat transfer mechanism that could occurred in the stratosphere can be considered. “The

stratosphere contains very dry air which is the medium that allows the presence of convection

in that layer of the earth atmosphere” (National Center for Atmospheric Research, 2009, ¶. 4). Natural convection was considered in the payloads inside, but at the outside forced convection

is the mean of heat transfer considered. For the analysis of natural convection at the payloads

inside the following terms were determined:

β = (1/T)ideal gas

GrL=

Pr =

Nu =

For the analysis of external forced convection at the payloads outside the following terms

were determined:

Nu =

Re =

The terms used in the convection analysis are mainly used to define the convection heat

transfer coefficient h which can be determine for different cases once the Nusselt number had

been evaluated.

The radiation in this analysis is only considered in the payloads inside and this is because the

structure in this analysis is examined in the coldest environment that can occur only during

night. For the evaluation of radiation in the payload the following equation was used:

represents the variation of the

density of a fluid with temperature

at a constant pressure.

represents the ratio of the buoyancy

force to the viscous force acting on

the fluid. (Grashof number)

represents the ratio between the

velocity boundary layer and the

thermal boundary layer form in the

contact surface between a fluid and

a solid surface. (Prandtl number)

Dimensionless convection heat

transfer convection (Nusselt

number)

represents the enhancement of heat

transfer through a fluid layer as a

result of convection relative to

conduction across the same fluid

layer.

represents the ratio between the

inertial forces and the viscous

forces. Used to determine the fluid

flow regime. (Reynolds number)


Qrad eq = єFR4 σAeq (Ts4- Tin

4)

A summary of the analysis performed is presented in the appendix. The results obtained show

that for this application 5 W of heat are lost from the payload’s inside. This were the results

obtained from the analysis of the coldest environment that the payload can experience. The

other case that was considered was the worst warm case that the payload can experiment. The

measures considered to protect the payload for this case involve the use of reflective material

in the walls of the payload’s external structure to reflect a considerable portion of the sun rays

received and also the walls of the external structure in its inside will be polished to improve

the emissivity of the material so that the rate of heat transfer that moves from the inside to the

outside can be increased. A table that illustrates how this surface treatment can change the

emissivity of the material is the following:

Aluminum 0C Emissivity

Unoxidized 100 0.03

Commercial Sheet 100 0.09

Roughly Polished 100 0.18

Table 10: Effects of the surface treatment in the emisivity

4.6 Mechanical Design

The first step in the mechanical design was to determine which type of aluminum alloy was

the appropriate for this application. This alloy was selected considering that the structures

have to withstand thermal and mechanical loads during the various mission phases. Weight

was another important parameter considered for the material selection, since there is a

maximum value of mass that can’t be exceeded in this project (i.e. 3kg). The materials

examined are presented in the following table:

Aluminum ρ (Mg/m³) (Mpa) (Mpa) K ( /m

6066-T6 2.71 255 131 167

2014-T6 2.79 414 172 154

2014-T4 2.79 290 262 134

7075 2.8 220 150 130

1060 2.7 83 55 234 Table 11: Alloy Selection

The aluminum 6061-T6 was the alloy selected for this application because of its advantages

compared with the other materials. As can be observed from the table this material posses the

best combination of thermal and mechanical properties necessary for this application. In

addition Polystyrene Foam was the insulating material selected for this project. Polyester

foam was selected because of its low cost and low conductivity (i.e. 0.08W/mK). These

characteristics are what make this material a good option for heat transfer problems,

specifically for applications with weight limitation. The payloads geometry selected is

basically a cube; this symmetrical geometry facilitates the structural and thermal analysis of

the payload as well as the computation of any unknown dimension. The cube structure made


of aluminum will be form using assembling methods that basically consist of joining

aluminum square pieces using l shape brackets. This structure was selected considering the

maintenance of the structural stresses within a considerable range during the payload’s ascent

and descent.

4.6.1 External Structure

The external structure is basically a cube used to provide the first thermal and mechanical

protection to the equipment inside the payload. It’s a box built with polystyrene insulation in

its core and aluminum skin at its outside. The external aluminum structure is constituted of

four sides that are made using the aluminum alloy 6061 which is a common type of alloy used

for space applications where the weight and resistance of the materials are important factors.

The top cover of the external structure is also made from aluminum and is attached to the rest

of the structure using brackets. The bottom cover is provided by HASP personnel and is

attached to the rest of the structure using the same type of brackets used for the sides and top

parts of the payload’s structure. An illustration of the payload’s wall is provided in the

following figure:

Figure 49:Payload”s Top Cover

The previous figures is used to illustrate the basic components of the payload structure. As

can be observed from the figure the payload’s walls will be painted with a reflective color at

its outside surface and at the inside surface will be treated to increase the emissivity of the

aluminum so that the payload’s heat transfer rate from the inside can be increased. These

features will help to prevent any overheating of the internal components due to the

stratosphere’s environment. A complete illustration of the payloads external structure is

shown in the following figure:


Figure 50: Internal View of the External Structure

The mounting plate will be attached to the payload’s external structure using L-shape

brackets. The following figure is used to illustrate this feature.

Figure 51: External Structure Drawing

As can be observed from the previous figure four L-shape brackets will be used to secure the

payload to the mounting plate. This amount of couplers will create a strong bond between the

mounting plate and the payload’s structure, which is required for the structure, since the

payload will be exposed to a 10 g vertical and 5 g horizontal shock. An analysis was made

using two different software (i.e. Solidworks and ANSYS) to determine the stresses develop

during the payload flight whit the purpose of verifying that the structure is capable enough to

resist the stresses developed in its components during its flight. Figures that illustrate the

results obtained from these analyses are the following:


Figure 52: Finite Element Analysis View 1

Figure 53 Finite Element Analysis View 2

The payload’s walls were analyze separately considering the correspond load of each wall,

that is a vertical shock of approximately 2.5 g and a horizontal shock of 5 g. The 2.5 g of

vertical load comes from the fact that there will be 4 walls that act like columns supporting the

10 g of vertical shock. By inspection of the counter plots shown in the figures above it can be

appreciated that as expected there will be a stress concentration in the regions near the holes

for the bolts due to the area discontinuities in that section (i.e. less area supporting the stress).

However, both contour plots show that the payload’s walls are capable of withstanding the

stresses developed during the payload’s flight and this can be observe because the dominant

color in both plots is blue, which represent in the plot’s scale the lower values of stress. The

complete external structure with its dimensions is presented in the following figure:


Figure 54: Detail drawings of payload

4.6.2 Internal Structure

The internal case is used to provide thermal and structural support for the internal components

which are in this case electronic devices. The internal case is basically a box build using

polyester foam. The foam will be utilized as an insulation and also as a damper for any impact

that the electronic components could experience during the payload’s flight. The internal case

has the same geometry and building concept used in the external structure, but with a

difference in building materials and dimensions used. An example of how the payload should

look from the its top is illustrated in the following figure:

Figure 55: Top view payload structure

Insulation External

Structure

Electronic

Components L-shape

Brackets


Is important to mention that a set of holes will be made in the internal structure to route the

electrical cables to the payload’s inside. These cables are necessary for the electrical and data

connections. The polyester foam used for the internal case is a material commonly used for

payloads missions. The following table contain a list of important properties of the polyester

foam:

Polyester Foam Properties

Density Thermal

Conductivity

Specific Heat Young Modulus Tensile Strength

1050 kg/m3 0.08 W/(m-K) 1.3 kj/kg.k 3000 MPa 46-60MPa

Table 12 Polyester Properties

The figure # contains a complete description of the payload’s inside structure with all the

dimensions and necessary views:

Figure 56: View of punctures on structures

The internal structure will be protected by the external structure which withstand all the loads

directly and by the insulation material that enclose this part of the payload. All the important

dimensions and drawing views of the external structure are provided in the following figure:

Figure 57: Internal Structure Drawing


4.6.3 Mass Budget

In this project the maximum mass allowed for a small payload is 3kg. The approximate value

of the total mass of our payload is 2682.05g. This total mass was determined using values

obtained from the Solidworks (CAD software) mass properties feature and considering

approximated values for the PCBs and microcontroller (i.e. Arduino). The masses obtained

directly from the software were the insulation, the external structure and the internal structure.

The value of

the PCBs were base in past experiment of this kind. To eliminate any bias introduced by the

presumed mass values of the PCBs and to work in conservative range of values, the mass

value of the PCBs observed in previous experiment was increased from 95g to 100g for each

board. Also the mass value of the microcontroller board was approximated to 100g. The

following table is used to show the payload’s main components and their masses.

Component Mass (grams)

External Structure 950.29

Internal Structure 616.41

Insulation 815.35

Two PCB (approximately) 200

Arduino 100

Total Mass 2682.05

Table 13: Mass Budget

It can be observed considering the total mass value, that even with the increment of mass in

the PCB values we still have 317.95g that can be used for any component that is not

considered in this moment.

5.0 Payload Development Plan

Prior to the payload fabrication in the development phase various task should accomplished

such as verifying calculations, designs, prototyping and testing. This is done to resolve issues

that can only be fulfilled through testing results made to the prototype. The areas that will be

mostly focused on will be software, electrical and mechanical.

On the software, tests and measurements will be obtained to identify the size of files

developed when storing data to the SD card. It is necessary to establish the processing time of

the program which is obtained by prototyping. Verify that all interfaces, connections, and

programming will work as plan, otherwise apply the suitable contingency plan previously

develop. Simulate or develop a model to ensure that the microcontroller can communicate

through proper connections that will be used for telemetry purpose.

The electrical section will involve prototyping the signal conditional for the external

temperature sensor and the sun sensor to verify the output response and perform calibrations.

Develop the complete design of the print circuit board and develop a prototype. Perform the

prototyping and calibration for the temperature sensor. Proving that the degrees calculated

with the sun sensor data are approximately identical to the sun positioning measured.


Mechanical prototyping will be performed to ensure optimal quality in the payload’s structure.

Test will be performed to ensure the thermal characteristics calculated are similar to the

characteristics and behavior physically.

For the prototyping parts are necessary to be order with a degree of urgency thus requiring a

organize list of parts with sequence. The order the part must be order is:

1. Arduino

2. Magnetometer

3. Gyroscope

4. Accelerometer

5. Slot and SD Memory Card SDHC compatible

6. Payload Structure materials

More detail on order or purchase of parts can be observe in the table in section 10.1

6.0 Payload Construction Plan

When we have the component dimensions we will start sketching for a box that meets the size

and making an estimate of the weight. After the sketching we will start making possible real

size models and testing then. When we finish with the result we will make the final box and

test it with all of the components.

6.1 Hardware Fabrication and Testing

The hardware fabrication will be worked in parallel since the measurement of the payload

enclosure is known, allowing the members to start their respective sections. There will be

various tests done in the mechanical section such as thermal, impact, stress, strain and

vibration. On the electrical part there will be test in current and power dissipation, verifying

that circuits work properly. In the software development there will be a test of all sensors to

make sure it is giving and storing the proper data. The parts and components will be ordered

as soon as possible to prevent shipping delays. If a delay were to happen the team will work

on other areas accordingly until the parts are received to reduce downtime.

6.2 Integration Plan

A mechanical interface mounting plate will be provided to for the payload. The thickness of

the mechanical interface mounting plate is ¼” PVC. The payload will be enough attached to

the mounting plate that can handle 10g vertical and 5g horizontal shock. The mounting plate

includes an EDAC 516-020 connector for power. The EDAC connector will be the power

interface between the payload and the HASP platform.


Figure 58: EDAC pin layout

The EDAC 516 for HASP has twenty pins as shows Figure 54. The pins function and the

color code for the wires of the EDAC 516 are explained in the Table 13.

Function EDAC Pins Wire Color

30VDC A, B, C, D White with red stripe

Power Ground W, T, U, X White with black stripe

Analog 1 K Blue

Analog 2 M Red

Signal Return L, R Black

Discrete 1 F Brown

Discrete 2 N Green

Discrete 3 H Red with white stripe

Discrete 4 P Black with white stripe Table 14: EDAC 516 pins function and color code

As shows Table 1, the +30VDC delivered power from the HASP platform can be received

through the pin A, B, C and D of the EDAC 516 interface and the ground can be provided by

the pins W, T, U and X.

6.3 Software Implementation and Verification

The first step is to design the program to meet the Pro 328 needs and run it for testing

purposes. The sensor code will be develop separately and tested to verify proper functionality,

then the code structure will be develop to join all the different sensor code and tests with the

complete code. If errors and problems appear they will be verified for electrical errors, if no

electrical errors code will be corrected.

This phase will be executed as follow:

Determine the required bytes

Flowchart analysis

Sensor calibration

Display sensor data during testing

Verify Arduino’s processing time


6.4 Flight Certification Testing

To certify that the ADS payload is ready for flight it is necessary to reproduce test with

conditions that could occur during flight, such as pressure, temperature changes and impact

test when the payload is lands. By doing this prevents possible failures that can occur, such

electrical failure due to any of the different conditions just mentioned.

The following tests were concluded:

Vacuum Test

The testing will be done by:

Styrofoam to hold the sensors in place

Full system test

o Payload shock testing

o Payload temperature

o Payload vacuum testing

Electrical system testing

o PCB board continuity test

o Cable connection testing

o Electronic components test (IC- integrated circuit testing)

6.4.1 System Testing Procedures

Vacuum Test

The vacuum test was performed with in a vacuum chamber with the capability of (35psi) in

the physics and astronomy department as shown in Figure 59.

Figure 59 Psi Vacuum chamber

The payload was placed in the chamber, sealed and the test was initiated. The test was

fulfilled by raising the pressure by a factor of 10 up to 30psi, for each pressure the payload

was left for 10 min as the pressure raised and as it went down to cero.

Temperature Test

This test requires placing the payload in four different temperatures stages, starting from the

highest to the lowest temperature and then at the same rate reducing the temperature to the

lowest. First it was placed outside at ambient temperature for 10min then it was placed at

room temperature 25oC, then it was place in a freezer for 10mins and then it will be place in a


box with dry ice. Then the same procedure will be performed until the temperature is finally

ambient temperature. Figure 60 shows the box where it was placed with dry ice.

Figure 60 Chamber where temperature test was taken

Shock test

The shock test consist of dropping the payload while fully functional and talking data, from a

height of approximately 10 feet as shown in Figure 61.

Figure 61: Shock Test


6.4.2 System Testing Results

Vacuum Test

During the time payload was tested it operated correctly during the complete test, the values

obtained will be shown in the Table in Appendix D. The complete test the payload

successfully kept gathering data and function properly... The values of the sensor remained

throughout the test the same…. In the result analysis after the calibration the data will be

plotted and explained in detail. It is important to identify that the output is raw data, later it

will be converted to significant values for each sensor.

Temperature Test

Throughout the temperature test the payload was being exposed to different temperatures for

a determined period of time. The results of the data will be in Appendix D, the results should

show that the all the components function properly during the complete test. The data that will

have change will be the temperature; this data will be plotted as a temperature vs time

analysis. Also plots of sensor data vs. temperature will be completed.

Shock Test

For the shock test the result showed that the payload is capable of a withstanding the impact

while taking data from the sensor without failure. In Appendix D the table shown has the

values obtained during this test. By observing the values it can be observed the electrical

components and the structure is capable of passing the impact test.

7.0 Mission Operations

Equipment final checkup

Complete system integration

Place the equipment on the launch site

Ground platform tracking

Data analysis

o Data retrieval

o Data conversion

o Data plots

o Plot analysis

7.1 Pre-Launch Requirements and Operations

A successful flight testing in simulated environment (similar to that were the payload is going

to be, such as vacuum and thermal testing) will be done to make sure that the sensors are

working as expected. The Arduino also needs to boot up and run the pre-flight software to

ensure the memory will be clean, in other words with 0 data in the SD card.

7.1.1 Calibrations

Proper sensor calibration, with the recommended procedure suggested by the manufacturer,

needs to be done to all of the sensors in the ADS payload.


Magnetometer Calibration

Calibration of the MicroMag3 is necessary to comprehend the raw data obtained by the

attitude determination system, to obtain orientation. Calibration will be made by using a

Helmholtz Coil shown in Figure 62, this payload is centered with two large coils (Helmholtz

coils) to receive a uniform magnetic field.

Figure 62 Helmholtz coils

By placing the ADS payload in the center of the coil it is possible to compare the values of the

magnetometer with the calculated values of the field in the Helmholtz. The field in the

Helmholtz is calculated with the following equation:

Where

B= Magnetic filed in Teslas

µ0= Magnetic permeability of vacuum in N/A2

N= number of turns

I = current in Amperes

R= radius of the coil in meters

The Helmholtz has an N of 70 turns and a radius for the coils of 26.4cm; with the power

supply it is possible to find the magnetic field by knowing the current. The following equation

is a simplified form of the previous equation to obtain the field magnitude with a controlled

current.

This test was done with the MM3 without ADS payload, the result obtained when the current

was cero was approximately 400counts and with a current of 1A the output was approx. 8400

on the positive x-axis similar, the count of the magnetic field was 8000counts. By applying

the following we obtained a gain of 33.58counts/µT, this values is similar to the gain on the

datasheet of 31.24counts/ µT.

MM3


Notice on Table 14 the x-axis has values much larger than the other axis, because this is the

concerning one at this instant.

X Y Z

8407 357 489

Table 15 Example of raw data from the MM3

To convert the raw data all that needs to be done is to multiply the counts of the axis and

multiply it by the gain calculated for that axis. For the each axis the same procedure must be

done.

The calibration values based on the data obtained at each axis both on the positive side and

negative side can be obtained with the equations in Table 15.

Xoffset= Xmax+ Xmin

Calculates the Offset Yoffset= Ymax+ Ymin

Zoffset= Zmax+ Zmin

Xrange= Xmax- Xmin

Calculates the Range Yrange= Ymax- Ymin

Zrange= Zmax- Zmin Table 16: Calibration values

Where

Xmax & Xmin are the maximum and minimum values obtained in the X-axis

Ymax & Ymin are the maximum and minimum values obtained in the Y-axis

Zmax & Zmin are the maximum and minimum values obtained in the X-axis

To correct the offset the following equations in Table 16 must be applied to the values of the

magnetometer.

Xvalue = Xraw - XOffset

Yvalue = Yraw - YOffset

Zvalue = Zraw - ZOffset Table 17: Equations to correct offset

Note that if the values of the Xrange are greater than the Y range it is necessary to match the

gain by using the following equation:

Since tan-1

results is only in the range of 0 to 90 it is important to note the sign of the X and Y

to determine the proper quadrant and to add the correct padding to determine it direction, this

is assisted by using the values in Table 17.

X value Y value Formula Quadrant

D= Ө +X +Y 0-90

D=180 - Ө -X +Y 90-180


D=180+Ө -X -Y 181-270

D=360 - Ө +X -Y 271-359 Table 18: Quadrant determination

To obtain the calibration equations the values obtained from the magnetometer are plotted and

compared with the known magnetic field of the Helmholtz as in Figure 63.

Figure 63: Helmholtz coil (X) vs MM3 (Y)

With figure # it can be observe the a linear fit for the set data will allow a calibration equation

which is

F=0.9624(DCounts) – 25.40

Where

F = Helmholtz field

DC= Digital Counts (raw data)

Digital Temperature Sensor (DS18B20)

As mentioned in Section 3.4.1 Technical Background and 4.3.1 Sensors Subsystem, the

internal temperature of the payload will be gathered using a DS18B20 Digital Temperature

Sensor. The DS18B20 will be calibrated by placing this sensor with a calibrated temperature

sensor

(HOBO) inside the payload and exposing the payload to a temperature profile. These

measurements will be stored during the temperature profile to develop a graph with both

measures and compare the readings of the DS18B20 with the reading of the calibrated

temperature sensor. A plot can be generated using both measurements to obtain an equation to

adjust the output of the DS18B20 and calibrate the data obtained from this sensor; as a result,

the data of the DS18B20 will be calibrated in the post flight analysis phase using the gathered

equation to realize some adjustments to the output of the DS18B20.


The temperature profile consists of the following environments; ambient temperature outside

the building, ambient temperature inside the building, inside the fridge and inside the freezer.

The payload will be on each environment for approximately 30 minutes. In addition, after the

payload complete 10 minutes in the freezer it will return to the fridge for 10 minutes and to

the other environments that it was previously exposed to complete a temperature profile.

The calibrated temperature sensor that will be use is a HOBO, which is an indoor data logger

that can measure and record temperature measurements. The temperature readings of the

HOBO can be obtained using the software of the HOBO data logger and generate a plot of the

temperature profile that the payload will be expose. In addition, the readings of the DS18B20

will be plotted to study the response of this instrument. The DS18B20 has a 1 wire interface

and requires one port pin for communication. Through this pin data can be obtained and the

Pro 328 can be send pulses to the DS18B20.

The Pro 328 can be programmed to adjust the output of the DS18B20 sensor from the DQ pin

after the payload has been retrieved and the data has been downloaded from the micro SD

memory. A transaction sequence is required to establish communication with the DS18B20,

which is explained in detail in the DS18B20 datasheet.

The DS18B20 has the following temperature register format;

BIT 7 BIT 6 BIT 5 BIT 4 BIT 3 BIT 2 BIT 1 BIT 0

LS BYTE

BIT 15 BIT 14 BIT 13 BIT 12 BIT 11 BIT 10 BIT 9 BIT 8

MS BYTE S S S S S

Where; S = Sign

LS BYTE = Least significant Byte

MS BYTE = Most significant Byte

The Pro 328 will read the temperature measures of the DS18B20 during flight; the raw data is

in digital format using both least significant byte and the most significant byte as shows the

Table above. The DS18B20 will measure temperature in digital format. BIT 11 is will indicate

the sign of the reading to determine if the measured temperature is a negative or a positive

value. When S = 0 the value is positive and for negative values S = 1. The subsequent

equations are required to shift the data from two bytes into a word and to convert the measures

from digital quantities into physical quantities. The data shifting is realized using the

following equation;

Where; MSB = the Most Significant Byte

LSB = the Least Significant Byte

For a positive number (When S = 0) the temperature reading from the DS18B20 in digital

format can be converted into a temperature value using the following equation;


For a negative number (When S = 1) the temperature reading from the DS18B20 in digital

format can be converted into a temperature value using the following equation;

The temperature measurements are placed from BIT 4 to BIT 11; however, the code for the

DS18B20 will shift 16 bit number, so that the measure will start at BIT 0 instead of BIT 4; as

a result, the measurement value will be from BIT 0 to BIT 7.

Table 19: DS18B20 versus HOBO temperature measures

The Table 18 shows simulated measurements obtained from both; the DS18B20 temperature

sensor and the HOBO during the temperature profile. Both sensors were inside the payload

during the temperature profile. For the temperature profile the payload remained on each of

the five different environments; ambient temperature outside the building, ambient

temperature inside the building, the fridge, the freezer and the dry ice for approximately 10

minutes.

HOBO data (°C) DS18B20 data (°C)

30 28

20 18

10 7

5 4

-10 -12

5 4

10 7

20 18

30 28


Figure 64: Linear Fit

Figure 64 shows the temperature measurements from both sensors; the DS18B20 and the

HOBO temperature sensor. This graph was developed using the Graphical Analysis 3.2

software. Note that there is a small difference between the temperature measures of the

DS18B20 and the HOBO measures; therefore, an equation is required to make fine

adjustments to the change the output values from the sensor into a calibrated response.

The subsequent equation is required to convert the measures from digital quantities into

physical quantities. This equation was obtained using the data and the Graphical Analysis

software;

Where; The temperature measured by the DS18B20

The raw data of the DS18B20

The gain

The Offset

Accelerometer Calibration

The SCA3000 Three axis accelerometer sensor will have an output response when a

capacitance change occurs due to acceleration. Once the accelerometer sensor arrives the

prototype for the accelerometer sensor will be implemented to perform the required tests. The

accelerometer prototype will be exposed to at least three different acceleration positions on

each one of its axes to determine the output response of the sensor at that particular

acceleration. The next step is to assign a digital value to each one of the selected outputs

response of the accelerometer to obtain a linear equation that will relate the outputs with the

digital values.

Gyroscope Calibration


The ITG-3200 Three axis gyroscope sensor will measure the rate of rotation; as a result, the

sensor will have an output response when sense a change in rotation in each one of the axis.

Each axis will be rotated at approximately the same rate of rotation to have a similar

calibration for each axis. After rotating each axis at a particular rate of rotation and obtain the

output response, a linear equation can be created to relate the digital values with the

gyroscope output response.

7.1.2 Pre-Launch Checklist

Make sure all the instruments are working properly

Realize a final check of the prototype comparing it with the schematics and the

simulations

Revise the list of test, such as thermal and vacuum test to ensure that all the testing has

been accomplish

Run all the program and make sure are working properly

Bring all the necessary equipment for any emergency

7.2 Flight Requirements, Operations and Recovery

The payload will ascend up to an altitude of 120,000 ft for approximately 2 hours and remain

there for 16 hours total. The payload and components will have to support temperature

conditions of an expected -40 degree of temperature. The system needs the sensors to read all

the time to get all the data during the flight. The batteries must be able to support the flight

with the minimum required power. If the batteries are not in the minimum required power

then the circuit would be in equilibrium with the sensor voltage required for them to work.

The experiment needs a GPS or any radiofrequency tracking device of high power so we can

track the altitude in which the payload is located and to track the retrieval of the payload in

the landing site.

7.3 Data Acquisition and Analysis Plan

The Arduino Pro requires an SD card memory module for the storage of the data during the

flight then we going to download the data using an Arduino Pro and a serial/USB cable in

which is going to be connected from the payload to the computer software but to process the

receiving data we need to convert the measurement in ADC counts requiring some equations

for the convection of ADC to physical values then we analyze the data of the atmosphere and

flight of the payload.

7.3.1 Ground Software

The ground software requires the following components; a microcontroller (Atmega 328), a

serial/USB cable, the code to download the data and a computer to process the information

and download the data from the payload. Graphical analysis 3.2 for plot the data will also be

needed.

7.3.2 Data Analysis Plan


The first step on the ground station after the land will be to use the post flight program to take

the data from the payload. The software will be prepared using the Arduino IDE. We will

implement some software for the calibration of the sensors. The data will be store using ADC

counts to represent the measurements from the sensors. In the process of receiving the data,

the ADC will convert the measurements into ADC counts that will be stored in the SD card.

This requires some equations to convert from ADC counts to physical values. Some

uncertainties during the launch are expected as well as in the balloon cut off and in the

landing. Expecting those irregularities, make some extra calibrations looking for the most

precise measurements.

8.0 Project Management

To ensure documentation version control a single team member (A.M. Espinal Mena) will be

the team member that will have the latest version of all the documentation. It has been agreed

that when a team member do a modification in the PDR, CDR and FRR they have to send an

e-mail of the modification to this team member, so she can add it to the proper document and

send a notification to the rest of the team so they can now which parts has been updated. In

addition to the days of class regular meetings in the week to monitor the progress of the

project will be scheduled.

8.1 Organization and Responsibilities

The EQUIS Team consists of three students of the Inter American University of Puerto Rico,

Bayamón Campus. The responsibilities of these students are to work on the following part of

their experiment; the electrical/mechanical designs, prototype development, fabrication,

integration and testing of the payload that will be launch with a balloon. The name of the

students of the EQUIS Team and their tasks are as follows:

A. M. Espinal Mena, [email protected], Electrical Design, Prototype and

Calibration

E. M. Portilla Matías, [email protected], Software Design and Implementation

F. O. Rivera Vélez, [email protected], Mechanical and Thermal Design

J. I. Espinosa Acevedo, [email protected], Prototype and Calibrstion, Risks

and Management plan

8.2 Configuration Management Plan

Every time a design is made we consult with the team member so we can make a decision of

the design and to analyze de advantage and disadvantage of the design before getting

approved.

8.3 Interface Control

Interface control allows us to maintain a constant monitoring of the Flight Readiness Review

(FRR) document at all times. It was established in a group meeting to assign one person in

charge of the FRR, this person will be in charge of constantly adding new information to the

document and uploading its final version, this way every member will allow access to the file.

Also an online group section was established where all document will be uploaded. It was

notified to the members that every time a document is uploaded or any change will be made to

mailto:[email protected]





notify Ana Espinal through a call, which is the person in charge of the FRR, doing so she will

be aware of any modifications. Finally a group meeting will be held to verified the complete

document and ensure it is the final version before submitting.

9.0 Master Schedule

We establish to divide the tasks into different member of the team but some task will be in

parallel with the other task, because this will makes us to meet the experiment goal. The

amount of days assigned to each task is shown in the Figure 62. Following the work

breakdown schedule is essential to realize the mission of this experiment.

9.1 Work Breakdown Structure (WBS)

Figure 65: WBS- Work Breakdown Schedule

Figure 65 shows the WBS of the EQUIS team to complete the EQUIS payload and

instruments on time.

9.2 Staffing Plan

A. M. Espinal Mena- Electrical design, Prototype and Calibration

E. M. Portilla Matías- Software Design and Implementation

F. O. Rivera Vélez- Mechanical and Thermal Design

J. I. Espinosa Acevedo- Prototype and Calibrstion, Risks and Management plan

Advisor: Dr. H. B. VO/ E. G. Delgado


9.3 Timeline and Milestones

The PDR, CDR and FRR documents have to be submitted by the following deadlines:

PDR- Preliminary Design Review due March 5, 2010

PDR Revision- Preliminary Design Review Revision due April 12, 2010

PDR Defense- Preliminary Design Review Defense June 4, 2010

CDR- Critical Design Review due July 1, 2010

FRR- Flight Readiness Review due July 23, 2010

10.0 Master Budget

The maximum capital cost budget required for this project is $5,000. It is also required to

have a reserve contingency fund of 10%, which is $500 in this case; therefore, the capital cost

budget is $4,500.

10.1 Expenditure Plan

Integrating the instruments for the ADS experiment requires several components. Table 13

shows the list of electronic components necessary to integrate the instruments, their price and

delivery status.

Lead time Sensors Part Number

Sales Company

Quantity Status Price ($)

1 Three Axis Accelerometer

SCA3000 Sparkfun 2 - $89.98

($44.99

each)

1 Three Axis Gyroscope

ITG-3200 Sparkfun 2 - $99.90

($49.95

each)

1 Three Axis Magnetometer

Micromag3 Sparkfun 2 - $119.90

($59.95

each)

1 Digital Temperature Sensor

DS18B20 Sparkfun 2 - $8.50

($4.25each)

1 Level Shift Converter

8745 Sparkfun 10 - $19.50

($1.95 each)

1 San Disk 4 GB SDSDB-

004GA14F

Amazon 2 - $17.98 ($8.99)

1 Arduino Pro DEV-09221 Sparkfun 2 - $39.90 ($19.95 each)

1 microSD transflash

BOB-00544 Sparkfun 2 - $29.90 ($14.95 each)

1 Material for housing - $500


11.0 Risk Management and Contingency

Risk Type Risk

Assessment of Risk Risk Control

Measures Impact Severity Likelihood Probability

Detention Difficulty

Electrical

Exceed component’s temperature

HIGH HIGH MEDIUM Provide a

heating system

Faulty connection

between cables HIGH HIGH MEDIUM

Ensure connections

and strap cable to prevent movement

Short circuit HIGH MEDIUM MEDIUM Review the PCB

population process

SD card failure HIGH LOW MEDIUM Transmit through

Telemetry

Mechanical

Temperature Leakage into

payload HIGH MEDIUM MEDIUM

Pressure and temperature

testing

Structure Failure HIGH LOW MEDIUM

Minimize apertures, use alloy 2014 and

mono-block design

Loosening of nuts and bolts

due to vibration MEDIUM LOW LOW

Use pressure bolts

Fall into wet terrain

HIGH MEDIUM LOW Ensure proper

sealing of Payload

Software

Data Corruption HIGH HIGH HIGH Store Data in SD

memory card

Loss of Data due to

Overwriting HIGH HIGH MEDIUM

Divide SD in sectors of 512bytes

Improper Logic Programming

HIGH MEDIUM HIGH Test program before flight

1 Extra PCB board - $300

1 Real Time Clock DS1306 Maxim 2 - $12.72

($6.36 each)

-- Total Cost: - $1364.18

Table 20: Materials Acquirement & Costs


Insufficient memory storage

HIGH HIGH LOW Obtain memory

card with greater storage

Scheduling

Not meeting FRR deadline

HIGH MEDIUM MEDIUM

Getting more hours of work and more days

in the lab

Errors in FRR HIGH MEDIUM MEDIUM Review

document various time

Table 21: Risk Management & Contingency

Through a risk management it is possible to reduce the likelihood of unexpected events. By

having a contingency plan it is possible to reduce costs and severity of a risk. This is done by

identifying, assessing and developing a strategy to response for each risk, while monitoring

for additional risks as shown in Figure 66. Table 14shows the potential risks that the EQUIS

experiment may encounter and the contingency plan that the ADS team has for each of these

risks. As illustrated in the Table 14, the potential risks have several categories. It is important

to keep constant cycle of risk management in order to control possible variables that may

affect project performance.

Figure 66: Risk Management Cycle


12.0 Glossary

CDR Critical Design Review

FRR Flight Readiness Review

PDR Preliminary Design Review

TBD To be determined

TBS To be supplied

WBS Work breakdown structure

HASP High Altitude Student Platform

ITS Internal Temperature Sensor

ADS Attitude Determination System

EQUIS Experiment with Quality United In Science

NEU North-East-Up

MRI Magnetic Resonance Imaging

GPS Global Positioning Satellite

SD Secure Digital

USB Universal Serial Bus

EEPROM Electrically Erasable Programmable Read-Only Memory

ADC Analog to Digital Converter

FET Field Effect Transistor

IC Integrated Circuits

PCB Printed Circuit Board

LSB Least significant byte

MSB Most significant byte


Appendix

Appendix A

I. Data.

Tout = -800C Qemt eq = 1W (computed)

Tin = 00C (design parameter) kalm = 134W/m

0C

kins = 0.12 W/m0C Lalm = 0.0032m

Lins = 0.005m σ = 5.67X10-8W/m2K

4 (Stefan-Boltzmann const.)

єFR4 = 0.8 єAlm = 0.07 (rough surface)

ѵair@100000ft = 8.012X10 – 4 m2/s Vmean@100000ft = 26.82m/s

ρair@100000ft = 1.841X10-2 kg/m3 μair@100000ft = 1.475X10-5 kg/m s

II. Find

Qloss = ?

III . Diagrams

Figure 67: Heat Loss Analysis


IV. Analysis

Heat loss:

Qloss =UA∆T ∆T= (Tin – Tout), UA= , Rtotal = Req1+RA1,1+ Rins+RAl2+Req2

Thermal Resistances:

Req2 = hcomb = hrad,in + hconv,in hconv,in = ? ; hrad,in = ?

Equipment power radiation:

Qrad eq = єFR4 σAeq (Ts4- Tin

4) Ts =Tin +

Ts=450K=1820C; Aeq=0.01198m

2

Qrad eq = hradAeq (Ts- Tin ) hrad,in = = 0.27W/m

2 0C

Internal Convection:

NuL = = ; L =0.1m ;

s=0.06m (distance between boards)

Ra,s = ; B = ; g@100,000ft=9.715m/s2

Tf = = 150C = 288K ; B = 0.003472/K; Pr=0.7362; k=0.02364W/m

0C

Ra,s = 530.19 RaL= Ra,s (L3/s

3) = 306.82

NuL =1.79 = hconv=0.71W/m0C hcomb,in ≈ 1W/m

2 0C

Therefore:

Req2 = 83.5 0C/W

Req1 = hcomb = hrad,out + hconv,out hrad,out = ? hconv,out = ?

Qrad out = єAlm σAs (Ts4- Tout

4) = 84.8mW, hrad,out = = 0.15W/m

2 0C

-0.5

Ideal

gas


For external convection:

Walls modeled as:

Figure 68: External Convention

Re = where Lc = L Re = 4686 = 4.69X103

Recr =5X10

5 Re < Recr (laminar flow regime)

Therefore:

Nu = = 0.664 ReL0.5

Pr1/3

With interpolation a Pr = 0.7394 is obtained

Nu = 41.1 h = 5.51 W/m2 0

C hcomb = 5.66 W/m2 0

C Req1 = = 9.710C/W

Rcond, eq = Alm,out + ins + Alm,in = 3.31 0C/W

Rtotal = Req1+ Rcond, eq +Req2 =96.52 0C/W UA= = 0.0104W/

0C

Qloss for each side is

Qloss =UA∆T= 0.78W (considering the six sides) Qloss,max =6 Qloss W

Vmean

Tout Ts

L`


Appendix B

Sensors Subsystem Schematic and PCB design

Schematic design


PCB design


Appendix C

RTC (DS1306) pseudo code

spi_transfer(data)

SET SPDR to data

WHILE (NOT (SPDR AND (SET SPIF to 1))) DO

ENDWHILE

RETURN with SPDR

initializeRTC()

SET SPCR to enable SPI, master or slave, and clock frequency

SET slave select line to HIGH

input rtcRegister, setRtc_num

CALL spi_transfer with rtcRegister

CALL spi_transfer with setRtc_num

SET slave select line to LOW

receiveTimeStamp()

input time, rtcRegister, zero

SET zero to 0




CALL spi_transfer with zero RETURNING time

SAVE time to SD card



Magnetometer (MicroMag3) pseudo code

receiveMicroMagData()

FOR axis = 0 TO 2

SET SPCR to 0


SET reset line to LOW

SET reset line to HIGH

SET reset line to LOW

FOR bits = 0 TO 5

IF bits == 1 OR bits == 2 THEN

SET mosi line to HIGH

ELSE

SET mosi line to LOW

ENDIF

SET sclk line to HIGH

SET sclk line to LOW

ENDFOR

IF axis == 0 THEN







ELSE IF axis == 1 THEN







ELSE







ENDIF

WHILE data ready line == low DO

ENDWHILE

input firstBit


READ miso line RETURNING firstBit


input totalBits

SET totalBits to 0

FOR bits = 14 TO 0



input remainingBits

READ miso line RETURNING remainigBits


COMPUTE remainingBits as remainingBits << bits

COMPUTE totalBits as totalBits | remainingBits SET sclk line to LOW

ENDFOR


IF firstBit == 1 THEN

COMPUTE totalBits as totalBits - 32768

ENDIF


SAVE totalBits to SD card

ENDFOR


Accelerometer (SCA3000-D01) pseudo code

spi_transfer(data)

SET SPDR to data

WHILE (NOT (SPDR AND (SET SPIF to 1))) DO

ENDWHILE

RETURN with SPDR

receiveAcceData()

input data, rtcRegister,msb, lsb

COMPUTE rtcRegister as rtcRegister << 2




CALL spi_transfer with 0 RETURNING msb

CALL spi_transfer with 0 RETURNING lsb

COMPUTE data as (msb << 8) | (lsb & 0xf8) / 8

SAVE data to SD card



SD card pseudo code

createFile()

input fileName, counter

SET fileName[] as "EQUIS000.CSV"

FOR number to 1000

COMPUTE fileName[5] as number / 100 + '0'

IF counter >= 100 THEN

SET counter as 0

ENDIF

IF number >= 100 THEN

COMPUTE fileName[6] as counter / 10 + '0'

INCREMENT counter

ENDIF

IF number < 100 THEN

COMPUTE fileName [6] as number / 10 + '0'

ENDIF

COMPUTE fileName[7] as number % 10 + '0'

IF fileName == false THEN

BREAK

ENDIF

ENDFOR

WRITE to fileName ",header"

saveData()

input data

CALL sensorFunction returning data

WRITE to fileName ","

WRITE to fileName data


Pre-flight software: /****************************

*

*

* Pre-flight

* EQUIS software

*

*****************************/

/////////////PINS//////////////

#define MISO 12

#define MOSI 11

#define SCK 13

#define RTCPIN 8

/////////////Variables/////////

byte secs;

byte mins;

byte hrs;

byte date;

byte day;

byte month;

byte year;

byte clr = 0; // used to clear data

char spi_transfer(volatile char data)

SPDR = data; // SPDR = Atmega's SPI data register

/********************************

* SPIF is bit 7 of the SPSR

* When a serial transfer is complete

* the SPIF flag is set

**********************************/

// SPSR = Atmega's SPI status register, SPIF = SPI interrupt flag

while (!(SPSR & (1 << SPIF)))

// wait until transmission is complete

;

/************************************

* SPDR is used for data transfer

* between the register file

* and the SPI shift register

************************************/

return SPDR; // return SPI data register

void set_RTC(byte register_num, byte time)

//SPCR = 0;

register_num |= 128;

/**************************************

* RTC DS1306

* SPI protocol

* sampled falling edge

* SPCR = Atmega's SPI control register

***************************************/

// SPE = enable SPI

// MSTR = sets arduino in master mode


// SPI mode 1

SPCR = (1 << SPE) | (1 << MSTR) | (1 << CPHA);

clr = SPCR; // clear data from past runs

clr = SPDR; // clear data from past runs

digitalWrite(RTCPIN, HIGH); // (slave) select rtc

spi_transfer(register_num); // transfer register

spi_transfer(time); // transfer data to set time

digitalWrite(RTCPIN, LOW); // (slave) deselect rtc

Serial.println("Done");

byte get_RTC(byte register_num)

//SPCR = 0;

register_num &= 127;

/**************************************

* RTC DS1306

* SPI protocol

* sampled falling edge


***************************************/

byte temp; // temporary variable

// SPE = enable SPI


// CPHA = clock phase, sample data = falling or rising

// SPI mode 1

SPCR = (1 << SPE) | (1 << MSTR) | (1 << CPHA);



digitalWrite(RTCPIN, HIGH); // (slave) select rtc


temp = spi_transfer(0); // transfer zero to receive data from

register

digitalWrite(RTCPIN, LOW); // (slave) deselect rtc

return temp;

void setup()

Serial.begin(9600); // set baud rate

pinMode(MOSI, OUTPUT);

pinMode(MISO, INPUT);

pinMode(RTCPIN, OUTPUT);

pinMode(SCK, OUTPUT);

pinMode(9, OUTPUT); // magnetometer

pinMode(7, OUTPUT); // accelerometer

pinMode(10, OUTPUT); // SPI sd card

pinMode(2, OUTPUT); // magnetometer reset

digitalWrite(RTCPIN, LOW); // use RTC, active-high

digitalWrite(10, HIGH); // SPI, active-low

digitalWrite(9, HIGH); // disable


digitalWrite(7, HIGH); // disable

/**************************

* clear the control register

* before any write

* write protect is in the 6th

* bit of the control register

*****************************/

set_RTC(0x8F, 0x04); // set RTC control register to 0

byte temp = get_RTC(0x0F);

Serial.print("ControlReg: "); Serial.println(temp, HEX);

set_RTC(0x80, 0x00); // set seconds write register to 0

set_RTC(0x81, 0x40); // set the minutes to 40min

set_RTC(0x82, 0x23); // set hours to 11pm to 24 hr = 23

set_RTC(0x83, 0x01); // (monday = 1, tuesday = 2, etc)

set_RTC(0x84, 0x19); // set date to the 19th

set_RTC(0x85, 0x07); // month

set_RTC(0x86, 0x10); // year 00-99

void loop()

month = get_RTC(0x05); // get month

year = get_RTC(0x06); // get year

day = get_RTC(0x03); // get day

date = get_RTC(0x04); // get date

hrs = get_RTC(0x02); // get hours

mins = get_RTC(0x01); // get minutes

secs = get_RTC(0x00); // get seconds

// Display output

switch (day)

case 1:

Serial.println("Monday");

break;

case 2:

Serial.println("Tuesday");

break;

case 3:

Serial.println("Wednesday");

break;

case 4:

Serial.println("Thursday");

break;

case 5:

Serial.println("Friday");

break;

case 6:

Serial.println("Saturday");

break;

case 7:

Serial.println("Sunday");

break;

default:

Serial.println("Error");

break;


Serial.print("Mn/Dd/Yr: ");

Serial.print(month, HEX); Serial.print("/");

Serial.print(date, HEX); Serial.print("/");

Serial.print("20"); Serial.println(year, HEX);

Serial.print("Hr:Mm:Ss = ");

Serial.print(hrs, HEX); Serial.print(":");

Serial.print(mins, HEX); Serial.print(":");

Serial.println(secs, HEX);

delay(1000);


During flight software: /***************************************

*

*

* EQUIS Software

*

*

****************************************/

//////////header files/////////////

#include <SdFat.h> // SDFat lib

#include <SdFatUtil.h> // SDFat lib

#include <OneWire.h> // temperature sensor

#include <Wire.h> // I2C library, gyroscope

////////////objects///////////////

Sd2Card card; // sd card

SdVolume volume; // sd card

SdFile root; // sd card

SdFile file; // sd card

OneWire tempSens(3); // temperature sensor pin 3

//////////////variables//////////////

byte clr = 0; // clear registers

int acc_data = 0; // accelerometer

char rtc_data = 0; // RTC

int totalBits = 0; // magnetometer

int firstBit = 0; // magnetometer

#define GYRO_ADDR 0x69 // gyro address binary = 1101001

#define SMPLRT_DIV 0x15 // gyro smaple rate register

#define DLPF_FS 0x16 // gyro sets range and low pass filter

#define INT_CFG 0x17 // gyro interrupt register

#define PWR_MGM 0x3E // gyro power management

#define SYNC_INTERVAL 1000 // mills between calls to sync

#define LOG_INTERVAL 1000 // mills between entries

uint32_t syncTime = 0; // time of last sync()

// calculate temperature celcius

int msb = 0;

int lsb = 0;

int total = 0;

int signBit = 0;

int temperature = 0;

int degrees = 0;

int fraction = 0;

///////////////Pins/////////////////

#define MOSI 11

#define MISO 12

#define SCK 13

#define ACCEPIN 7

#define ACCE_RESET 6

#define RTCPIN 8

#define MAGNEPIN 9

#define MAGNE_RESET 2

// function for the sd card

// outputs error on screen

#define error(s) error_P(PSTR(s))

void error_P(const char *str)


PgmPrint("error: ");

SerialPrintln_P(str);

if (card.errorCode())

PgmPrint("SD error: ");

Serial.print(card.errorCode(), HEX);

Serial.print(',');

Serial.println(card.errorData(), HEX);

while(1);

//initializes the gyroscope

void initGyro()

/*****************************************

* ITG 3200

* power management set to:

* clock select = internal oscillator

* no reset, no sleep mode

* no standby mode

* sample rate to = 3Hz

* parameter to +/- 2000 degrees/sec

* low pass filter = 5Hz

* no interrupt

******************************************/

Wire.beginTransmission(GYRO_ADDR);

Wire.send(PWR_MGM);

Wire.send(0x00);

Wire.endTransmission();


Wire.send(SMPLRT_DIV);

Wire.send(0xFF); // EB, 50, 80, 7F, DE, 23, 20, FF



Wire.send(DLPF_FS);

Wire.send(0x1E); // +/- 2000 dgrs/sec, 1KHz, 1E, 19



Wire.send(INT_CFG);

Wire.send(0x00);


char spi_transfer(volatile char data)

SPDR = data; // SPDR = Atmega's SPI data register

/********************************

* SPIF is bit 7 of the SPSR

* When a serial transfer is complete

* the SPIF flag is set

**********************************/

// SPSR = Atmega's SPI status register, SPIF = SPI interrupt flag

while (!(SPSR & (1 << SPIF)))

// wait until transmission is complete

;

/************************************


* SPDR is used for data transfer

* between the register file

* and the SPI shift register

************************************/

return SPDR; // return SPI data register

void getMagnetometerData()

/****************************

* 3-axis Magnetometer

* MicroMag3

* pins used:

* Reset, Miso, Mosi

* SCK, Slave select

* SPI protocol

*******************************/

for(int axis = 1; axis <= 3; axis++)

// set control reg to zero to

// start using mag handshaking w/ Arduino

SPCR = 0;

digitalWrite(MAGNEPIN, LOW); // select magnetometer

delay(2);

// Toggle RESET low-high-low

digitalWrite(MAGNE_RESET, LOW);

delay(2);

digitalWrite(MAGNE_RESET, HIGH);

delay(2);


delay(2);

// giving commands to the micromag3

// first 6 bits of the command

// _________________________

//|DHST|PS2|PS1|PS0|ODIR|MOT|

//| 0 | 1 | 1 | 0 | 0 | 0 |

//|____|___|___|___|____|___|

// period select (PS2, PS1, PS0)

// of /2048

for(int bits = 1; bits <= 6; bits++)

if((bits == 2) || (bits == 3))

digitalWrite(MOSI, HIGH);

delay(2);

else

digitalWrite(MOSI, LOW);

delay(2);

digitalWrite(SCK, HIGH);

delay(2);

digitalWrite(SCK, LOW);

delay(2);

// next 2 bits for the complete 8 bits command


// last 2 bits determines the axis

// ___________

// ____ | X | Y | Z |

//| ASI| =| 0 | 1 | 1 |

//| ASO| =| 1 | 0 | 1 |

if (axis == 1) // Reading X axis, command

digitalWrite(MOSI, LOW); // ASI

delay(2);


delay(2);


delay(2);

digitalWrite(MOSI, HIGH); // ASO

delay(2);


delay(2);


delay(2);

else if(axis == 2) // Reading Y axis, command

digitalWrite(MOSI, HIGH); // ASI

delay(2);


delay(2);


delay(2);

digitalWrite(MOSI, LOW); // ASO

delay(2);


delay(2);


delay(2);

else // Reading Z axis, command

digitalWrite(MOSI, HIGH); // ASI

delay(2);


delay(2);


delay(2);

digitalWrite(MOSI, HIGH); // ASO

delay(2);


delay(2);


delay(2);

// instead of using the data ready pin

delay(500); // wait for data ready


delay(2);

firstBit = digitalRead(MISO); // first bit is for the sign,

//negative or positive

delay(2);



delay(2);

totalBits = 0; // clear variable

// Receive data byte

for(int bits = 14; bits >= 0; bits--)


delay(2);

int remainingBits = digitalRead(MISO);

delay(2);


delay(2);

remainingBits = remainingBits << bits; // shift data by

the //bit number

totalBits = totalBits | remainingBits;

digitalWrite(MAGNEPIN, HIGH); // magnetometer idle mode

delay(2);

// if negative, make data negative by subtracting integer value

//range (magnetometer)

if(firstBit == 1)

totalBits -= 32768;

// for testing purposes

if(axis == 1)

Serial.print("X = ");

else if(axis == 2)

Serial.print(" Y = ");

else

Serial.print(" Z = ");

// for the sd card to work

// SPI mode 0, leading edge = sample rising

// trailing edge = setup falling

// SCK frequency /128

SPCR = (1 << SPE) | (1 << MSTR) | (1<< SPR0) | (1<<SPR1) ;



delay(2);

file.print(","); file.print(totalBits);// first data is X axis,

second //Y axis, third Z axis

Serial.print(totalBits); // for testing purposes

byte RTC_Acc_Data(byte register_num, int pin)

/**************************************

* RTC DS1306


* Accelerometer SCA 3000-D01

* SPI protocol


***************************************/

byte temp; // temporary variable

if (pin == ACCEPIN)

register_num = register_num << 2;

// SPE = enable SPI








digitalWrite(pin, LOW); // select accelerometer

else // select RTC

register_num &= 127; // clear bit 7

// 127 = 01111111

// SPI mode 1, leading edge = setup rising

// trailing edge = sample falling

// SCK frequency /4

SPCR = (1 << SPE) | (1 << MSTR) | (1 << CPHA) ;



digitalWrite(pin, HIGH); // (slave) select rtc


temp = spi_transfer(0); // transfer zero to receive data from

register

if (pin == RTCPIN)

digitalWrite(pin, LOW); // (slave) deselect rtc

else

digitalWrite(pin, HIGH); // deselect accelerometer

// for the sd card to work







return temp;

void getGyroscopeData()

int gyro = 0;

/**************************************

Gyro ITG-3200 I2C

registers:

x axis MSB = 1D, x axis LSB = 1E

y axis MSB = 1F, y axis LSB = 20

z axis MSB = 21, z axis LSB = 22


**************************************/

// Arduino Wire library (I2C)


Wire.send(0x1D); // MSB x axis


Wire.requestFrom(GYRO_ADDR, 1); // one byte

byte msb = 0;

byte lsb = 0;

while(!Wire.available())

// wait for data to be available

;

msb = Wire.receive();


Wire.send(0x1E); // LSB x axis





;

lsb = Wire.receive();

// calculate total x axis

gyro = (( msb << 8) | lsb);

Serial.print(" gyroX= "); Serial.print(gyro);

file.print(","); file.print(gyro);

// clear variables

msb = 0;

lsb = 0;

gyro = 0;


Wire.send(0x1F); // MSB y axis





;



Wire.send(0x20); // LSB y axis




// wait!

;


// calculate total y axis

gyro = (( msb << 8) | lsb);

Serial.print(" gyroX= "); Serial.print(gyro);



// clear variables

msb = 0;

lsb = 0;

gyro = 0;


Wire.send(0x21); // MSB z axis




// wait...

;



Wire.send(0x22); // LSB z axis




// ...

;


// calculate z axis

gyro = (( msb << 8) | lsb);

Serial.print(" gyroZ= "); Serial.println(gyro);


void getTemperatureData()

/***************************

* 1-Wire digital thermometer

* DS18B20

****************************/

byte data[2]; // temperature data

tempSens.reset(); // initialization

tempSens.skip(); //Skip the device selection. This only works if you

//have a single device.

tempSens.write(0x44,1); // start conversion

delay(1000); // wait for conversion

tempSens.reset(); // initialization

tempSens.skip(); //Skip the device selection, This only works if you

//have a single device

tempSens.write(0xBE); // Read Scratchpad

file.print(",");

for ( int i = 0; i <= 2; i++)

// 3 bytes

data[i] = tempSens.read(); //read a byte


lsb = data[0]; // first byte

msb = data[1]; // second byte

total = (msb << 8) + lsb;

signBit = total & 0x8000; // 1000000000000000b

if (signBit) // if 1000000000000000b is true

// ^ XOR operator

// 1 ^ 1 = 0

// 0 ^ 1 = 1

total = (total ^ 0xffff) + 1; // 2's comp

temperature = (6 * total) + total / 4; // 0.0625

degrees = temperature / 100; // separate off the whole and fractional

portions

fraction = temperature % 100;

Serial.print(" Temp: ");

if (signBit) // If its negative

file.print("-");

Serial.print("-");

file.print(degrees);

Serial.print(degrees);

file.print(".");

Serial.print(".");

if (fraction < 10)

file.print("0");

Serial.print("0");

file.print(fraction);

Serial.println(fraction);

void setup()

Serial.begin(9600);

// Slaves as outputs

pinMode(MAGNEPIN, OUTPUT);

pinMode(ACCEPIN, OUTPUT);

pinMode(RTCPIN, OUTPUT);

// magnetometer specific pins

pinMode(MAGNE_RESET, OUTPUT);

// accelerometer specific pins

pinMode(ACCE_RESET, OUTPUT);

// Begin Wire library

Wire.begin();

// SPI specific for master/slave communication

pinMode(MOSI, OUTPUT);

pinMode(SCK, OUTPUT);

pinMode(MISO, INPUT);


//reset pins


digitalWrite(ACCE_RESET, HIGH);

// slaves deselected

digitalWrite(ACCEPIN, HIGH); // acce idle mode

digitalWrite(RTCPIN, LOW); // rtc idle mode

digitalWrite(MAGNEPIN, HIGH); // datasheet: HIGH = magnetometer in

idle //mode

//Setup gyroscope

initGyro();

// initialize the SD card

if (!card.init()) error("card.init");

// initialize a FAT volume

if (!volume.init(card)) error("volume.init");

// open root directory

if (!root.openRoot(volume)) error("openRoot");

// File Creation

int counter = 0; //

char fileName[] = "EQUIS000.CSV"; // file in comma separated values

//format

for (int num = 0; num < 1000; num++) // up to 999 files

fileName[5] = num/100 + '0';

if( counter >= 100)

counter = 0;

if (num >= 100)

fileName[6] = counter/10 + '0';

counter++;

if (num < 100)

fileName[6] = num/10 + '0';

fileName[7] = num % 10 +'0';

if(file.open(root, fileName, O_CREAT | O_EXCL | O_WRITE))

break;

if (!file.isOpen()) error ("file.create");

Serial.print("Logging to: ");

Serial.println(fileName);

// Sensor Headers

file.print("Date_Hr:Mm:Ss");

file.print(",mag_X"); file.print(",mag_Y"); file.print(",mag_Z"); //

3 //axis magnetometer

file.print(",acc_X"); file.print(",acc_Y"); file.print(",acc_Z"); //

3 //axis accelerometer


file.print(",gyr_X"); file.print(",gyr_Y"); file.print(",gyr_Z"); //

3 //axis gyroscope

file.print(",temp"); // temperature sensor

file.println(); // new line

if (file.writeError || !file.sync())

error("write header");

void loop()

file.writeError = 0;

delay((LOG_INTERVAL -1) - (millis() % LOG_INTERVAL));

// real-time clock

Serial.print("Date_Hr:Mm:Ss "); // testing

rtc_data = RTC_Acc_Data(0x04, RTCPIN); // receive date, HEX register

file.print(rtc_data, HEX); file.print("_");

Serial.print(rtc_data, HEX); Serial.print("_"); // testing

rtc_data = RTC_Acc_Data(0x02, RTCPIN); // receive hour, HEX register

file.print(rtc_data, HEX); file.print(":");

Serial.print(rtc_data, HEX); Serial.print(":"); // testing

rtc_data = RTC_Acc_Data(0x01, RTCPIN); // receive minutes, HEX

register

file.print(rtc_data, HEX); file.print(":");

Serial.print(rtc_data, HEX); Serial.print(":"); // testing

rtc_data = RTC_Acc_Data(0x00, RTCPIN); // receive seconds, HEX

register

file.print(rtc_data, HEX);

Serial.println(rtc_data, HEX); // testing

// magnetometer data

Serial.print("Mag: ");

getMagnetometerData();

Serial.println();

// accelerometer Data

byte lsb = 0;

byte msb = 0;

Serial.print("Acc: ");

msb = RTC_Acc_Data(0x05, ACCEPIN); // msb x axis

lsb = RTC_Acc_Data(0x04, ACCEPIN); // lsb x axis

acc_data = ((msb << 8) | (lsb & 0xf8)) / 8;

file.print(","); file.print(acc_data);

Serial.print("x = "); Serial.print(acc_data);

msb = RTC_Acc_Data(0x07, ACCEPIN); // msb y axis

lsb = RTC_Acc_Data(0x06, ACCEPIN); // lsb y axis



Serial.print(" y = "); Serial.print(acc_data);

msb = RTC_Acc_Data(0x09, ACCEPIN); // msb z axis

lsb = RTC_Acc_Data(0x08, ACCEPIN); // lsb z axis



Serial.print(" z = "); Serial.println(acc_data);

// gyroscope data

getGyroscopeData();

//Serial.println();


// temperature data

getTemperatureData();

file.println(); // new line

//don't sync too often - requires 2048 bytes of I/O to SD card

if ((millis() - syncTime) < SYNC_INTERVAL) return;

syncTime = millis();

if (!file.sync()) error("sync");


Appendix D

Shock Test Raw Data

Date_Hr:Mm:Ss mag_X mag_Y mag_Z acc_X acc_Y acc_Z gyr_X gyr_Y gyr_Z temp

22_13:43:1 -334 6 1275 241 -29 1327 3 72 -47 29.25

22_13:43:5 -262 39 1326 284 -121 1326 16 35 -21 29.31

22_13:43:9 -136 33 1304 219 -144 1323 -29 10 -15 29.25

22_13:43:13 -197 -4 1342 240 -130 1333 56 65 -78 29.31

22_13:43:17 -190 31 1236 -209 8 1382 179 306 -262 29.31

22_13:43:21 -477 -456 1248 -959 -359 288 987 3038 -1095 29.31

22_13:43:25 -470 1239 -209 -1297 -108 -223 8 33 -7 29.37

22_13:43:29 -470 1237 -209 -1299 -116 -226 10 34 -7 29.5

22_13:43:33 -470 1237 -208 -1299 -113 -224 10 34 -7 29.5

22_13:43:37 -468 1240 -208 -1296 -108 -225 9 34 -7 29.56

22_13:43:41 -469 1237 -209 -1300 -104 -235 9 33 -7 29.56

22_13:43:45 -469 1152 1280 -258 88 1444 -288 -213 721 29.62

22_13:43:49 -515 370 1185 -483 -43 1307 -10 19 283 29.56

22_13:43:53 -43 1087 794 -577 99 893 -363 172 -281 29.56

22_13:43:57 -355 -496 1051 -303 84 1305 239 120 -77 29.56

22_13:44:1 -74 -435 1116 -52 58 1335 13 100 -499 29.56

22_13:44:5 493 -332 1016 81 113 1360 -76 -200 -370 29.5

22_13:44:9 674 -59 1089 149 -61 1388 -51 88 27 29.5

22_13:44:13 648 -663 973 223 -7 1380 -65 69 -420 29.5

22_13:44:17 484 -479 1032 170 91 1356 8 38 -29 29.5

22_13:44:21 569 -291 1031 236 179 1310 85 49 -71 29.5

22_13:44:25 608 -116 1099 211 102 1346 -3 11 -9 29.5

22_13:44:29 589 -142 1095 150 132 1358 40 15 44 29.5

22_13:44:34 659 -124 1110 85 123 1363 28 66 53 29.5

22_13:44:38 644 125 1069 101 -98 1455 -304 50 -496 29.5

22_13:44:42 -645 -165 851 55 97 1350 -57 -18 19 29.5

22_13:44:46 -618 463 1006 -24 74 1363 11 35 -7 29.5

22_13:44:50 -619 461 1005 -29 72 1368 10 35 -6 29.56

22_13:44:54 -620 460 1006 -28 67 1370 11 35 -7 29.5

22_13:44:58 -620 462 1004 -26 74 1364 10 34 -6 29.5

22_13:45:2 -620 458 1003 -30 74 1351 10 35 -6 29.56

22_13:45:6 -615 472 1009 -29 73 1367 10 35 -6 29.56

22_13:45:10 -617 478 1009 -17 70 1364 10 35 -7 29.5

22_13:45:14 -614 468 1012 -24 72 1363 10 35 -5 29.56

22_13:45:18 -616 232 934 -133 129 1388 -103 -57 154 29.56

22_13:45:22 -551 191 731 79 127 1358 16 18 -36 29.56

22_13:45:26 -487 180 558 90 95 1365 -77 -12 122 29.56

22_13:45:30 -487 127 639 244 53 1330 6 58 -15 29.56

22_13:45:34 -475 -16 615 166 14 1302 -32 -76 14 29.62


22_13:45:38 -445 -28 453 -367 -241 3141 283 -151 -466 29.62

22_13:45:42 -477 757 1244 -35 149 1358 10 35 -6 29.56

22_13:45:46 -271 758 1238 -36 149 1354 11 35 -6 29.56

22_13:45:50 -271 757 1242 -30 146 1358 11 35 -6 29.62

22_13:45:54 -273 758 1241 -31 146 1359 11 35 -6 29.62

22_13:45:58 -273 759 1241 -41 145 1354 11 35 -6 29.62

22_13:46:2 -271 763 1253 233 144 1425 -117 59 -136 29.62

22_13:46:6 46 694 1334 -161 -13 1369 -41 -74 234 29.62

22_13:46:10 378 201 1304 -25 -6 1353 -21 26 54 29.68

22_13:46:14 626 -38 1309 -170 205 1352 156 -124 88 29.68

22_13:46:18 514 -51 1377 -9 115 1346 -37 80 -190 29.68

22_13:46:22 648 222 1297 -37 43 1350 29 -1 -58 29.68

22_13:46:26 672 283 1288 -26 19 1355 28 4 1 29.68

22_13:46:30 670 262 1361 -142 71 1404 -70 -70 43 29.68

22_13:46:34 530 75 1355 39 66 1345 -77 22 -31 29.68

22_13:46:38 581 167 1311 6 64 1383 72 -3 36 29.68

22_13:46:42 628 70 1324 75 99 1394 -127 102 258 29.68

22_13:46:46 570 -41 1358 80 192 1334 21 44 -8 29.75

22_13:46:50 512 -5 1366 79 218 1352 18 53 -7 29.75

22_13:46:54 516 -75 1347 131 178 1351 -1 49 -4 29.75

22_13:46:58 537 -81 1342 152 171 1357 57 69 -1 29.81

22_13:47:2 571 98 1303 179 -17 1314 106 112 -254 29.75

22_13:47:6 398 -515 1335 -54 41 1421 -345 111 -1139 29.81

22_13:47:10 325 633 948 -156 16 1457 40 194 133 29.81

22_13:47:14 619 -106 1161 -104 152 1384 82 83 22 29.81

22_13:47:18 662 120 1136 10 -167 1356 -1 3 687 29.81

22_13:47:22 -532 -103 827 414 -290 1267 58 474 -551 29.81

22_13:47:26 -831 1 1066 209 -40 1615 -271 176 -13 29.81

22_13:47:30 -793 -609 707 373 -110 1541 -50 -61 195 29.87

22_13:47:34 -492 -502 885 104 -9 983 216 95 87 29.87

22_13:47:38 24 -633 934 -104 216 1111 119 -137 163 29.87

22_13:47:42 -228 -635 577 -126 285 1236 -53 99 -438 29.81

22_13:47:46 -514 -540 721 -50 153 1738 -124 47 -298 29.81

22_13:47:50 -381 -689 807 49 66 994 -140 3 -103 29.87

22_13:47:54 -344 -478 368 20 -14 1330 165 -144 475 29.87

22_13:47:58 -658 387 776 146 287 1444 -1 223 -37 29.87

22_13:48:2 -554 338 668 127 247 1321 14 81 -102 29.87

22_13:48:6 -690 348 667 36 158 1354 -10 102 3 29.87

22_13:48:10 -716 208 645 15 100 1351 5 9 -12 29.93

22_13:48:14 -705 228 667 162 33 1369 -109 186 85 29.93

22_13:48:18 -640 181 659 62 226 1362 359 36 -308 29.93

22_13:48:22 -627 247 724 -23 103 1342 -47 153 -210 29.93

22_13:48:26 -724 186 572 166 -142 1352 -51 153 78 29.93

22_13:48:30 -733 345 734 -70 5 1481 -139 3 1096 30


22_13:48:34 441 982 704 -30 49 1367 13 36 -5 30

22_13:48:38 441 981 713 -27 43 1364 13 37 -5 30

22_13:48:42 429 967 710 -41 37 1361 19 46 -5 30

22_13:48:46 445 979 707 -33 53 1352 13 37 -5 30

22_13:48:50 446 980 764 101 163 1350 -31 14 -464 30

22_13:48:54 744 -342 778 -43 58 1363 13 36 -5 30

22_13:48:58 745 -339 772 -34 60 1362 13 38 -4 30.06

22_13:49:2 745 -331 762 -20 65 1365 14 36 -4 30.06

22_13:49:6 745 -337 787 -17 61 1368 13 36 -4 30.06

22_13:49:10 735 -333 784 -14 49 1355 13 36 -5 30.06

22_13:49:14 762 -353 770 -20 50 1353 2 18 -4 30.06

22_13:49:18 732 -334 798 -6 45 1366 10 34 -5 30.12

22_13:49:22 736 -342 785 -9 63 1366 20 47 -4 30.12

22_13:49:26 731 -336 780 1 124 1325 14 37 -4 30.12

22_13:49:30 754 -346 771 -51 58 1365 14 36 -4 30.12

22_13:49:34 761 -348 781 -21 69 1369 14 38 -4 30.18

22_13:49:38 767 -344 782 -59 37 1377 3 19 -4 30.12

22_13:49:42 760 -334 761 -20 62 1370 14 37 -4 30.18

22_13:49:46 765 -352 787 -31 58 1361 14 37 -4 30.12

22_13:49:50 766 -344 781 -17 61 1375 14 37 -4 30.18

22_13:49:54 739 -356 789 -30 67 1365 15 37 -4 30.18

22_13:49:58 747 -361 785 -18 54 1364 14 38 0 30.18

22_13:50:2 737 -370 785 -14 60 1364 15 38 -4 30.18

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