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Dynamic multipath mitigation applying unscented Kalman filters in local positioning systems

Published online by Cambridge University Press:  25 March 2011

Thorsten Nowak  and
Andreas Eidloth
Thorsten Nowak*
Affiliation:
RF and Microwave Design Department, Wireless Location Systems Group, Fraunhofer Institute for Integrated Circuits IIS, Nordostpark 93, 90411 Nuremberg, Germany. Phone:  + 49911 58061-3236.
Andreas Eidloth
Affiliation:
RF and Microwave Design Department, Wireless Location Systems Group, Fraunhofer Institute for Integrated Circuits IIS, Nordostpark 93, 90411 Nuremberg, Germany. Phone:  + 49911 58061-3236.
*
Corresponding author: T. Nowak Email: thorsten.nowak@iis.fraunhofer.de
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Abstract

Multipath propagation is still one of the major problems in local positioning systems today. Especially in indoor environments, the received signals are disturbed by blockages and reflections. This can lead to a large bias in the user's time-of-arrival (TOA) value. Thus multipath is the most dominant error source for positioning. In order to improve the positioning performance in multipath environments, recent multipath mitigation algorithms based upon the concept of sequential Bayesian estimation are used. The presented approach tries to overcome the multipath problem by estimating the channel dynamics, using unscented Kalman filters (UKF). Simulations on artificial and measured channels from indoor as well as outdoor environments show the profit of the proposed estimator model. Furthermore, the quality of channel estimation applying the UKF and the channel sounding capabilities of the estimator are shown.

Keywords

Wireless systems and signal processingAntennas and propagation for wireless systems
Type
Research Papers
Information
International Journal of Microwave and Wireless Technologies , Volume 3 , Special Issue 3: Special Issue on European Microwave Week 2010 , June 2011 , pp. 365 - 372
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2011

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