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Sensors 2015, 15(7), 17534-17557;

Collaborative WiFi Fingerprinting Using Sensor-Based Navigation on Smartphones

GNSS Research Center, Wuhan University, No.129 Luoyu Road, Wuhan 430079, China
Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N1N4, Canada
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 3 June 2015 / Revised: 4 July 2015 / Accepted: 10 July 2015 / Published: 20 July 2015
(This article belongs to the Section Physical Sensors)
Full-Text   |   PDF [4871 KB, uploaded 20 July 2015]   |  


This paper presents a method that trains the WiFi fingerprint database using sensor-based navigation solutions. Since micro-electromechanical systems (MEMS) sensors provide only a short-term accuracy but suffer from the accuracy degradation with time, we restrict the time length of available indoor navigation trajectories, and conduct post-processing to improve the sensor-based navigation solution. Different middle-term navigation trajectories that move in and out of an indoor area are combined to make up the database. Furthermore, we evaluate the effect of WiFi database shifts on WiFi fingerprinting using the database generated by the proposed method. Results show that the fingerprinting errors will not increase linearly according to database (DB) errors in smartphone-based WiFi fingerprinting applications. View Full-Text
Keywords: WiFi; indoor positioning; MEMS sensors; training; PDR WiFi; indoor positioning; MEMS sensors; training; PDR

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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

Zhang, P.; Zhao, Q.; Li, Y.; Niu, X.; Zhuang, Y.; Liu, J. Collaborative WiFi Fingerprinting Using Sensor-Based Navigation on Smartphones. Sensors 2015, 15, 17534-17557.

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