Dynamic Multipath Estimation by Sequential Monte Carlo Methods

Michael Lentmaier, Bernhard Krach, Patrick Robertson, and Thanawat Thiasiriphet

Abstract:	A sequential Bayesian estimation algorithm for multipath mitigation is presented, with an underlying movement model that is especially designed for dynamic channel scenarios. In order to facilitate efficient integration into receiver tracking loops it builds upon complexity reduction concepts that previously have been applied within Maximum Likelihood (ML) estimators. To demonstrate its capabilities under different GNSS signal conditions, simulation results are presented for both artificially generated random channels and high resolution channel impulse responses recorded during a measurement campaign.
Published in:	Proceedings of the 20th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2007) September 25 - 28, 2007 Fort Worth Convention Center Fort Worth, TX
Pages:	1712 - 1721
Cite this article:	Lentmaier, Michael, Krach, Bernhard, Robertson, Patrick, Thiasiriphet, Thanawat, "Dynamic Multipath Estimation by Sequential Monte Carlo Methods," Proceedings of the 20th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2007), Fort Worth, TX, September 2007, pp. 1712-1721.
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