An Adaptive Kalman Filter for a Range Measurement Based Indoor Positioning System: Algorithm Adaptation and Performance Testing

Sihao Zhao, Yang Jiao, Haipeng Mi, Tianyi Ma, Mingquan Lu

Peer Reviewed

Abstract:	To overcome the positioning inaccuracy and discontinuity due to the signal errors and user dynamics in a wireless indoor navigation system, an adaptive Kalman filter positioning algorithm is proposed. This adaptive method automatically tune the elements in the process and measurement variance-covariance matrices according to the innovation values to enable a varying dependence on process or measurement model. The theory of the method is presented based on which the parameter settings are discussed. Both static and dynamic experiments under real indoor environment are conducted to verify the proposed method. Iterative least square (ILS) and standard Kalman filter (KF) are introduced to compare with the proposed adaptive filter. Results show that the proposed method outperforms the ILS and KF in both positioning accuracy and continuity.
Published in:	Proceedings of the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2015) September 14 - 18, 2015 Tampa Convention Center Tampa, Florida
Pages:	2282 - 2290
Cite this article:	Zhao, Sihao, Jiao, Yang, Mi, Haipeng, Ma, Tianyi, Lu, Mingquan, "An Adaptive Kalman Filter for a Range Measurement Based Indoor Positioning System: Algorithm Adaptation and Performance Testing," Proceedings of the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2015), Tampa, Florida, September 2015, pp. 2282-2290.
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