Mitigating large errors in WiFi-based indoor localization for smartphones
Publication Type
Journal Article
Publication Date
11-2016
Abstract
Although WiFi fingerprint-based indoor localization is attractive, its accuracy remains a primary challenge, especially in mobile environments. Existing approaches either appeal to physical layer information or rely on extra wireless signals for high accuracy. In this paper, we revisit the received signal strength (RSS) fingerprint-based localization scheme and reveal crucial observations that act as the root causes of localization errors, yet are surprisingly overlooked or not adequately addressed in previous works. Specifically, we recognize access points' (APs) diverse discrimination for fingerprinting a specific location, observe the RSS inconsistency caused by signal fluctuations and human body blockages, and uncover the transitional fingerprint problem on commodity smartphones. Inspired by these insights, we devise a discrimination factor to quantify different APs' discrimination, incorporate robust regression to tolerate outlier measurements, and reassemble different normal fingerprints to cope with transitional fingerprints. Integrating these techniques in a unified system, we propose DorFin, i.e., a novel scheme of fingerprint generation, representation, and matching, which yields remarkable accuracy without incurring extra cost. Extensive experiments in three campus buildings demonstrate that DorFin achieves a mean error of 2.5 m and, more importantly, decreases the 95th percentile error under 6.2 m, both significantly outperforming existing approaches.
Keywords
Fingerprints, indoor localization, smartphones, WiFi
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
IEEE Transactions on Vehicular Technology
Volume
66
Issue
7
First Page
6246
Last Page
6257
ISSN
0018-9545
Identifier
10.1109/TVT.2016.2630713
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
WU, Chenshu; YANG, Zheng; ZHOU, Zimu; LIU, Yunhao; and LIU, Mingyan.
Mitigating large errors in WiFi-based indoor localization for smartphones. (2016). IEEE Transactions on Vehicular Technology. 66, (7), 6246-6257.
Available at: https://ink.library.smu.edu.sg/sis_research/4924
Additional URL
https://doi.org/10.1109/TVT.2016.2630713