Journal
SENSORS
Volume 15, Issue 7, Pages 17534-17557Publisher
MDPI
DOI: 10.3390/s150717534
Keywords
WiFi; indoor positioning; MEMS sensors; training; PDR
Funding
- National Natural Science Foundation of China [41174028, 41231174, 41325015, 41204029, 41375041]
- National 863 Program of China [2014AA123101]
- CSC Scholarship [201306270139]
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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.
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