Nowak T, Eidloth A (2011)
Publication Language: English
Publication Type: Journal article
Publication year: 2011
Publisher: Cambridge University Press
Book Volume: 3
Pages Range: 365-372
Journal Issue: 3
URI: http://like.eei.uni-erlangen.de/bib/Nowak2011_Dynamic.pdf
DOI: 10.1017/S1759078711000274
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. © 2011 Cambridge University Press and the European Microwave Association.
APA:
Nowak, T., & Eidloth, A. (2011). Dynamic multipath mitigation applying unscented Kalman filters in local positioning systems. International Journal of Microwave and Wireless Technologies, 3(3), 365-372. https://dx.doi.org/10.1017/S1759078711000274
MLA:
Nowak, Thorsten, and Andreas Eidloth. "Dynamic multipath mitigation applying unscented Kalman filters in local positioning systems." International Journal of Microwave and Wireless Technologies 3.3 (2011): 365-372.
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