NRSSD: Normalizing Received Signal Strength to Address Device Diversity Problem in Fingerprinting Positioning

doi:10.23940/ijpe.19.03.p33.10331044

Int J Performability Eng ›› 2019, Vol. 15 ›› Issue (3): 1033-1044.doi: 10.23940/ijpe.19.03.p33.10331044

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NRSSD: Normalizing Received Signal Strength to Address Device Diversity Problem in Fingerprinting Positioning

Chunxiu Li^a, Jianli Zhao^a,*, Qiuxia Sun^b, Xiang Gao^a, Guoqiang Sun^a, and Chendi Zhu^a

a School of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266000, China;
b School of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, 266000, China

Submitted on ; Revised on ;
Contact: zhaojianli@gmail.com
About author:Chunxiu Li is a master's student in the School of Computer Science and Engineering at Shandong University of Science and Technology. Her research interests include machine learning and indoor localization. Jianli Zhao received his Ph.D. in 2006 from the Department of Computer Application Technology at Northeastern University. In 2011, he served as an associate professor in the College of Computer Science and Engineering at Shandong University of Science and Technology. His current research interests include pervasive computing and indoor location.Qiuxia Sun received her Ph.D. in system theory in 2011 from Qingdao University. She is currently an associate professor in the College of Mathematics and Systems Science at Shandong University of Science and Technology. Her research interests include big data analysis.Xiang Gao is a master's student in the School of Computer Science and Engineering at Shandong University of Science and Technology. Her research interests include machine learning and indoor localization. Guoqiang Sun is a master's student in the School of Computer Science and Engineering at Shandong University of Science and Technology. Her research interests include machine learning and indoor localization.Chendi Zhu is a master's student in the School of Computer Science and Engineering at Shandong University of Science and Technology. Her research interests include machine learning and indoor localization.

Abstract

Abstract: The WiFi-based fingerprinting technique is widely adopted for indoor positioning due to its cost-effectiveness compared to other infrastructure-based positioning methods. However, the WiFi-based technique still faces the problem of device diversity in the application of an indoor positioning system. Previous studies have faced two main challenges. One is the curse of computational dimensionality in online positioning, while the other is the issue of low positioning accuracy in real applications. In this paper, we propose to normalize the observable Access Point (AP) signal strength to eliminate the influence of device diversity and avoid a dimension disaster. Experimental results show that our algorithm based on the normalization Received Signals Strength (RSS) not only solves the problem of device diversity but also outperforms three other baseline methods.

Key words: fingerprinting positioning, device diversity, normalization, positioning accuracy

Chunxiu Li, Jianli Zhao, Qiuxia Sun, Xiang Gao, Guoqiang Sun, and Chendi Zhu. NRSSD: Normalizing Received Signal Strength to Address Device Diversity Problem in Fingerprinting Positioning [J]. Int J Performability Eng, 2019, 15(3): 1033-1044.

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NRSSD: Normalizing Received Signal Strength to Address Device Diversity Problem in Fingerprinting Positioning

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