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Development of algorithms

Simulation of realistic transmitter and channel conditions

Receiver with template correlation and path detection

Support of for EU IP Pulsers WP3b

Localization errror analysis and simulation

Basis for integration of UWB and Inertial Measurement Unit

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localization and tracking

UWB system design

Jens Schroeder and Stefan Galler

Analysis of UWB Localization Errors

University of HannoverInstitute of Communications EngineeringLocation Based Services and Systems GroupHannover, Germany

� Simulation parameters

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PN=12 chip BPSK, f =8.25GHz, f =700MHz, f =80GSp/s

Pulse rate: , pulse train repetition rate:

Varying additive noise: =N (thermal noise) + 10 or 20dB

c LP s

N tσ2

repetition

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Pure statistical model

Space-variant model

System design

Simple NLOS detector

Tracking

(e.g. IEEE)

LOS error: Gaussian above real

value, additional noise adds

uniformly distributed error

NLOS error is statistic and does

not represent reflections

Unrealistic for tracking simulations

(e.g. IMST)

aspects

Processing gain (code length, SNR) vs. desired range

Range w/o “large” errors should be desired range

works quite well in realistic scenario:

Running variance ( ) > 10 cm²

aspects

Gaussian tracking filter (e.g. Kalman) not optimal for

uniformly distributed ranging errors

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� LOS error: either very accurate or uniformly distributed

NLOS error shows influence of reflections

Better suits reality for tracking simulations

1 second

Motivation

Future Work

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Increasing the number of channels for 3D-localization

Evaluation of different channel models

Incorporation of “hardware” Tx and Rx

Analysis of different synchronisation schemes

Development of localization and tracking filters

Integration of Inertial Measurement Unit

Localization Simulator

�

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Simulink model to simulate range estimates with varying

channel models and a virtual trajectory

Block diagram:

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A random walk of a mobile object within a given area using

the

The object is initially placed at a fixed position,

randomly chooses a new position, a velocity between 0.2-

0.7 m/sec and a pause time between 0.2-2 sec,

walks to the new location

and pauses, using the

chosen parameters.

The locations behind a virtual

wall are perceived to be ,

else

The resulting

is input to the channel model.

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random waypoint model

NLOS

LOS

virtual trajectory

[3]:

.

Virtual Trajectory

Results

ReceiverChannelTransmitter

PN

fc

fLP

Virtual

trajectoryfc±fLP

x-Corre-

lator

Path

detector

Channel

model

AWGN

σ2

N

� Implemented channel models

[1]: statistical model with parameters for

different envrionments. Here used: industrial LOS/NLOS

[2]: space-variant channel model with

spatial evolution of channel impulse responses. Here used:

office LOS/NLOS

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IEEE 802.15.4a

IMST whyless.com

PUL ERSPUL ERS∫

[1] A. F. Molisch, K. Balakrishnan, D. Cassioli, C.-C. Chong, S. Emami, A. Fort, J. Karedal, J. Kunisch, H. Schantz, U.Schuster, and K. Siwiak, "IEEE 802.15.4a channel model - final report," IEEE 2005.

[2] J. Kunisch and J. Pamp, "An ultra-wideband space-variant multipath indoor radio channel model," IEEE Conferenceon Ultra Wideband Systems and Technologies (UWBST), Reston, USA, 2003.

[3] D. B. Johnson and D. A. Maltz, "Dynamic Source Routing in Ad Hoc Wireless Networks," in , T.Imielinski and H. Korth, Eds.: Kluwer Academic Publishers, 1996.

[4] J. Schroeder, S. Galler, K. Kyamakya, and K. Jobmann, "Analysis and practical comparison of Wireless LAN andUltra-Wideband technologies for advanced localization," accepted at IEEE/ION Position, Location and NavigationSymposium (PLANS 2006), San Diego, USA, 2006.

Mobile Computing

Exemplary rangein industrial environment [4]

measurements

1ns

1100ms