Results from POD, RO profile collection, and processing from Spire's satellite constellationP. Platzer, D. Ector, O. Nogues Correig, and V. Irisov

Prepared for OPAC-IROWG 2016

OUTLINE• Current state of Spire

• Radio occultation scenario

• Data processing algorithm

• Precise orbit determination

• Statistical comparison with COSMIC

• Examples of atmospheric profile obtained by Spire

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POWERFULL SATELLITE CONSTELLATION• 17 satellites launched• 30+ satellites in space by year end• Completing up to 2 satellites per week• 21 ground stations globally• 30 ground stations by year end

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3

RADIO OCCULTATION SCENARIO

POD antenna

Forward ROantenna

Backward ROantenna

V

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DATA PROCESSING ALGORITHMRO phase

Bending angle and impact parameter

TEC and ionosphere compensation

Refractivity profile

Atmospheric profiles

Climatology model

Reference GPS data

RTorb: Precise Orbit Determination (POD)RO phase excess

The code is implemented in C++ with interprocess communication in Python.

Core RO processing code was developed by Michael Gorbunov(Spire contractor).

POD processing (RTorb) was developed by GPS Solutions (Christian Rocken)(Spire contractor) and licensed to Spire.

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PRECISE ORBIT DETERMINATION

LEO satellite orbital positions and velocities are determined by solving the equations of motion given a force model and GPS code and phase measurements

POD allows for precise computation of atmospheric phase delay on L1 and L2 frequencies

Force Model• Earth gravity field model

• Lunisolar perturbations

• Atmospheric drag

• Solar radiation pressure

GPS Observations and Corrections• Dual frequency code and phase

measurements

• GPS clock and orbit corrections with 5 second resolution

• Attitude corrections

Numerical Algorithm• Kalman filter approach to solve

equations of motion

• Backward smoothing

LEO positions/velocities

Excess L1/L2 atmospheric phase delay-Use dual frequency measurements of an occulting and a reference satellite-Remove effects of geometric range, tx/rx clock offsets, ionosphere to compute carrier phase delay due to the atmosphere

Overview of POD/Excess Phase Processing

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COMPARISON TO UCAR PROCESSING

• Spire POD processing results for a COSMIC satellite were compared to UCAR which uses Bernese POD software

• RMS differences of about 200 mm (position) and .2 mm/s (velocity) observed over 10 days

• Minor Spire/UCAR differences are likely due to details in POD processing

OVER 1 DAY OVER 10 DAYS

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Spire processing compared with CDAAC and ECMWF: “dry” temperature, 68000 profiles, 0-90˚lat., COSMIC orbits

Spire-CDAAC Spire-ECMWF CDAAC-ECMWF

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The same but with the Spire POD: 5900 profiles, 0-90˚lat.

Spire-CDAAC Spire-ECMWF CDAAC-ECMWF

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Spire processing compared with CDACC and ECMWF: “dry” temperature, 30000 profiles, 45-90˚lat., CDAAC orbits.

Spire-CDAAC Spire-ECMWF CDAAC-ECMWF

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The same but with the Spire POD: 2700 profiles, 45-90˚lat.

Spire-CDAAC Spire-ECMWF CDAAC-ECMWF

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RAW PHASE AND PHASE EXCESS MEASURED BY SPIRE FM2 (EXAMPLE 1)

550 600 650 700 750 800 850 900-7100

-7000

-6900

-6800

-6700

-6600

-6500

-6400

dPhs

/dt,

m/s

Time, s

L1 ion.L2 ion.L1L2

840 850 860 870 880 890 900-20

-10

0

10

20

30

40

50

60

70

80

Time, s

d/dt

(Pha

se e

xces

s), m

/s

ionosphere atmosphere

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ATMOSPHERIC TEMPERATURE PROFILE FROM SPIRE FM2 OBSERVATION (EXAMPLE 1)

The time difference between GFS profile and occultation event is 2.7 hours.

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150 200 250 3000

5

10

15

20

25

30

35

40

T, K

Z, k

m

NCEP GFSSpire

ATMOSPHERIC TEMPERATURE PROFILE FROM SPIRE FM2 OBSERVATION (EXAMPLE 2)

The time difference between GFS profile and occultation event is 3 hours.

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150 200 250 3000

10

20

30

40

50

60

T, K

Z, k

m

NCEP GFSSpire

10-6 10-4 10-2 100 1020

10

20

30

40

50

60

Water vapor, g/m3

Z,

km

NCEP GFS

• Radio occultation (RO) full chain data processing software was developed at Spire during the last 6 months. Advanced POD algorithm was implemented.

• Reprocessing of the COSMIC data shows the bias and standard deviation of the retrieved temperature profiles comparable with UCAR processing.

• Spire example profiles shown were collected summer 2016. Comparison with GFS data demonstrates the high quality of the retrieved atmospheric profiles.

• Spire objective is processing of large amount of the profiles on a daily basis.

• Algorithm and hardware improvement is going on…

CONCLUSIONS

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Acknowledgements. COSMIC data were provided by COSMIC Data Analysis and Archive Center.