RSS Fingerprint Based Indoor Localization Using Sparse Representation with Spatio-Temporal Constraint.
The Received Signal Strength (RSS) fingerprint-based indoor localization is an important research topic in wireless network communications. Most current RSS fingerprint-based indoor localization methods do not explore and utilize the spatial or temporal correlation existing in fingerprint data and measurement data, which is helpful for improving localization accuracy. In this paper, we propose an RSS fingerprint-based indoor localization method by integrating the spatio-temporal constraints into the sparse representation model. The proposed model utilizes the inherent spatial correlation of fingerprint data in the fingerprint matching and uses the temporal continuity of the RSS measurement data in the localization phase. Experiments on the simulated data and the localization tests in the real scenes show that the proposed method improves the localization accuracy and stability effectively compared with state-of-the-art indoor localization methods.
Beijing Advanced Innovation Center for Future Internet Technology, Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing 100124, China. piaoxinglinphd@emails.bjut.edu.cn.
Xinglin
X
Piao
Beijing Advanced Innovation Center for Future Internet Technology, Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing 100124, China. zhangyong2010@bjut.edu.cn.
Yong
Y
Zhang
Beijing Advanced Innovation Center for Future Internet Technology, Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing 100124, China. yuqingqing@emails.bjut.edu.cn.
Tingshu
T
Li
Beijing Advanced Innovation Center for Future Internet Technology, Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing 100124, China. huyongli@bjut.edu.cn.
Yongli
Y
Hu
Beijing Transportation Information Center, Beijing 100073, China. hao.liu@bjjtw.gov.cn.
Hao
H
Liu
Beijing Transportation Coordination Center, Beijing 100073, China. zhangke@bjjtw.gov.cn.
Ke
K
Zhang
Beijing Advanced Innovation Center for Future Internet Technology, Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing 100124, China. geyun@bjut.edu.cn.
Yun
Y
Ge
RSS fingerprint; indoor localization; sparse representation; spatial constraint; temporal constraint