WCSE

Wi-Fi fingerprint Localization Using RSSI-probability Radio Map

Abstract— Location-Based Service has moved into indoor scene by mature Wi-Fi network infrastructure and intelligent handheld terminal device development in decade years. Traditional indoor localization systems is designed by RSSI fingerprint mechanism to estimate user location. This paper indicated the limitation of pure RSSI by analysing the RSSI performance in experiment and proposed an RSSI-Pro transformation algorithm for radio map construction. To verify the desired accuracy an actual indoor localization system called LocNeedle is designed to implement the method of this article. LocNeedle adopts Bhattacharyya distance as similarity measurement metric to find the target user location, which can achieve that the 95% of localization error distance is under 2.5 meters while 70% is under 1 meter.

Index Terms— Wi-Fi Localization, RSSI Probability Distribution, Similarity Measurement, Bhattacharyya distance.

Yue Guo, Zhiqing Huang
School of Software Engineering, Beijing University of Technology, CHINA
Jun Lei
Beijing Engineering Research Center for IoT Software and Systems, CHINA

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Cite: Yue Guo, Zhiqing Huang, Jun Lei, "Wi-Fi fingerprint Localization Using RSSI-probability Radio Map," 2015 The 5th International Workshop on Computer Science and Engineering-Information Processing and Control Engineering (WCSE 2015-IPCE), pp. 387-393, Moscow, Russia, April 15-17, 2015.