Context-aware Adaptive Extended Kalman Filtering Using Wi-Fi Signals for GPS Navigation

Mahsa Shafiee, Kyle O'Keefe and Gerard Lachapelle

Abstract:	Due to the ever-growing coverage of WLAN networks, integrating Wi-Fi and GPS can be a promising approach to solving problems encountered by precise indoor GPS positioning such as severe multipath. In this paper, the question of indirect use of WLAN signals and exploiting the external information provided by Wi-Fi signals is addressed. One possible way to exploit knowledge of changes in user context is with adaptive positioning methods where the Wi-Fi information can be used to adjust uncertain parameters in the GPS positioning algorithm. The use of external information in a context-aware programming framework to improve GPS positioning performance within the navigation solution is investigated. A new two-layer adaptive extended Kalman filter positioning algorithm is proposed based on multiple model adaptive estimation. An algorithm based on the Dempster-Shafer theory is proposed to fuse decision sequences of several identifiers to increase the probability of correct context identification. The algorithm is then modified to deal with high conflict situations and correlative decisions. Furthermore, to improve the robustness of the proposed context-aware algorithm a control block based on the type 2 finite state Markov Decision Process (MDP) is implemented with regard to the reward history in which a reward is realized based on the one-step transition between identified contexts in two consecutive epochs.
Published in:	Proceedings of the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2011) September 20 - 23, 2011 Oregon Convention Center, Portland, Oregon Portland, OR
Pages:	1305 - 1318
Cite this article:	Shafiee, Mahsa, O'Keefe, Kyle, Lachapelle, Gerard, "Context-aware Adaptive Extended Kalman Filtering Using Wi-Fi Signals for GPS Navigation," Proceedings of the 24th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2011), Portland, OR, September 2011, pp. 1305-1318.
Full Paper:	ION Members/Non-Members: 1 Download Credit Sign In