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Micromachines 2015, 6(3), 347-363; doi:10.3390/mi6030347

Smartphone-Based Indoor Integrated WiFi/MEMS Positioning Algorithm in a Multi-Floor Environment

Chongqing Key Lab of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
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Author to whom correspondence should be addressed.
Academic Editors: Naser El-Sheimy and Aboelmagd Noureldin
Received: 22 December 2014 / Revised: 18 February 2015 / Accepted: 24 February 2015 / Published: 3 March 2015
(This article belongs to the Special Issue Next Generation MEMS-Based Navigation—Systems and Applications)
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Abstract

Indoor positioning in a multi-floor environment by using a smartphone is considered in this paper. The positioning accuracy and robustness of WiFi fingerprinting-based positioning are limited due to the unexpected variation of WiFi measurements between floors. On this basis, we propose a novel smartphone-based integrated WiFi/MEMS positioning algorithm based on the robust extended Kalman filter (EKF). The proposed algorithm first relies on the gait detection approach and quaternion algorithm to estimate the velocity and heading angles of the target. Second, the velocity and heading angles, together with the results of WiFi fingerprinting-based positioning, are considered as the input of the robust EKF for the sake of conducting two-dimensional (2D) positioning. Third, the proposed algorithm calculates the height of the target by using the real-time recorded barometer and geographic data. Finally, the experimental results show that the proposed algorithm achieves the positioning accuracy with root mean square errors (RMSEs) less than 1 m in an actual multi-floor environment. View Full-Text
Keywords: multi-floor positioning; WiFi fingerprinting; MEMS; extended Kalman filter multi-floor positioning; WiFi fingerprinting; MEMS; extended Kalman filter
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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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MDPI and ACS Style

Tian, Z.; Fang, X.; Zhou, M.; Li, L. Smartphone-Based Indoor Integrated WiFi/MEMS Positioning Algorithm in a Multi-Floor Environment. Micromachines 2015, 6, 347-363.

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