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Sensors 2015, 15(12), 31244-31267;

An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones

Institute of Remote Sensing and GIS, Peking University, No. 5 Yiheyuan Road, Haidian District, Beijing 100871, China
National Remote Sensing Center of China, No. 8A, Liulinguan Nanli, Haidian District, Beijing 100036, China
Beijing Aerospace Unmanned Vehicles System Engineering Research Institute, No. 1 Fengyingdong Road, Haidian District, Beijing 100094, China
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 5 October 2015 / Revised: 3 December 2015 / Accepted: 4 December 2015 / Published: 11 December 2015
(This article belongs to the Section Sensor Networks)
Full-Text   |   PDF [8222 KB, uploaded 11 December 2015]   |  


Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF) algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel “quasi-dynamic” Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the “process-level” fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR) positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move. View Full-Text
Keywords: indoor positioning; Wi-Fi; PDR; multi-sensor fusion; TCPF indoor positioning; Wi-Fi; PDR; multi-sensor fusion; TCPF

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Li, H.; Chen, X.; Jing, G.; Wang, Y.; Cao, Y.; Li, F.; Zhang, X.; Xiao, H. An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones. Sensors 2015, 15, 31244-31267.

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