Probabilistic Multipath Mitigation for GNSS-based Vehicle Localization in Urban Areas

Marcus Obst, Christian Adam, Gerd Wanielik, Robin Schubert

Abstract:	Reliable and accurate positioning is a core requirement for many automotive applications. In this paper, a Bayesi-an satellite-based localization algorithm for vehicles is presented. In order to solve this problem in dense urban areas, multipath situations need to be handled carefully. Therefore, the main contribution of this work is a proba-bilistic multipath mitigation strategy which can be used in online scenarios. The positioning algorithm described in this work will be tested and validated with real data rec-orded during a test drive under typical urban conditions. To assess the positioning performance, the results will be compared to a highly reliable reference sensor. It will be shown that the proposed algorithm autonomously ex-cludes suspicious observations and decreases the position-ing error down to 50 percent even when using low-cost single frequency receivers.
Published in:	Proceedings of the 25th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2012) September 17 - 21, 2012 Nashville Convention Center, Nashville, Tennessee Nashville, TN
Pages:	1454 - 1461
Cite this article:	Obst, Marcus, Adam, Christian, Wanielik, Gerd, Schubert, Robin, "Probabilistic Multipath Mitigation for GNSS-based Vehicle Localization in Urban Areas," Proceedings of the 25th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2012), Nashville, TN, September 2012, pp. 1454-1461.
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