Collaborative WiFi Fingerprinting Using Sensor-Based Navigation on Smartphones

Sensors

Peng Zhang¹  Qile Zhao¹  You Li¹  Xiaoji Niu¹  Yuan Zhuang²  Jingnan Liu¹ 

[1] GNSS Research Center, Wuhan University, No.129 Luoyu Road, Wuhan 430079, China; E-Mails:;Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N1N4, Canada; E-Mail:

关键词: WiFi;    indoor positioning;    MEMS sensors;    training;    PDR;   

DOI  :  10.3390/s150717534

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.