Particle Filter and Clustering Based Robust Positioning Algorithm in the WiFi Weak Signal Environment

Beomju Shin, Bosun Yu, Jaewon Bang, Jeahun Kim, Taikjin Lee

Abstract: To estimate a position in the indoor environment, WiFi positioning system (WPS) is useful technology in view of positioning performance, cost, availability. Especially, particle filter (PF) present a stable performance by integrating WiFi signal and sensor output such as accelerometer and gyroscope. But the initial positioning error remains a problem. In this paper, we propose the pattern matching algorithm and clustering approach to correct the initial positioning error. To make a weak WiFi environment, we utilize only 20% installed access point (AP). We identify that the proposed algorithm makes a stable positioning performance than the conventional PF.
Published in: Proceedings of the 2017 International Technical Meeting of The Institute of Navigation
January 30 - 2, 2017
Hyatt Regency Monterey
Monterey, California
Pages: 116 - 122
Cite this article: Shin, Beomju, Yu, Bosun, Bang, Jaewon, Kim, Jeahun, Lee, Taikjin, "Particle Filter and Clustering Based Robust Positioning Algorithm in the WiFi Weak Signal Environment," Proceedings of the 2017 International Technical Meeting of The Institute of Navigation, Monterey, California, January 2017, pp. 116-122. https://doi.org/10.33012/2017.14965
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