Dynamic multipath mitigation applying unscented Kalman filters in local positioning systems

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Nowak T, Eidloth A
Title edited volumes: European Microwave Week 2010, EuMW2010: Connecting the World, Conference Proceedings - European Wireless Technology Conference, EuWiT 2010
Publication year: 2010
Conference Proceedings Title: Wireless Technology Conference (EuWIT), 2010 European
Pages range: 9 -12
ISBN: 9781424472338
ISSN: 2153-3644
Language: English


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 show the profit of the proposed estimator model. © 2010 EuMA.



FAU Authors / FAU Editors

Eidloth, Andreas
Professur für Informationstechnik (Schwerpunkt Ortsbestimmung und Navigation)
Nowak, Thorsten
Lehrstuhl für Informationstechnik mit dem Schwerpunkt Kommunikationselektronik (Stiftungslehrstuhl)


How to cite

APA:
Nowak, T., & Eidloth, A. (2010). Dynamic multipath mitigation applying unscented Kalman filters in local positioning systems. In Wireless Technology Conference (EuWIT), 2010 European (pp. 9 -12). Paris.

MLA:
Nowak, Thorsten, and Andreas Eidloth. "Dynamic multipath mitigation applying unscented Kalman filters in local positioning systems." Proceedings of the Wireless Technology Conference (EuWIT), 2010 European, Paris 2010. 9 -12.

BibTeX: 

Last updated on 2018-09-08 at 22:39