Communications and Networking. 11th EAI international Conference, ChinaCom 2016 Chongqing, China, September 24-26, 2016, Proceedings, Part II

Research Article

RSSI Based Positioning Fusion Algorithm in Wireless Sensor Network Using Factor Graph

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  • @INPROCEEDINGS{10.1007/978-3-319-66628-0_55,
        author={Wanlong Zhao and Shuai Han and Weixiao Meng and Zijun Gong},
        title={RSSI Based Positioning Fusion Algorithm in Wireless Sensor Network Using Factor Graph},
        proceedings={Communications and Networking. 11th EAI international Conference, ChinaCom 2016 Chongqing, China, September 24-26, 2016, Proceedings, Part II},
        proceedings_a={CHINACOM},
        year={2017},
        month={10},
        keywords={Wireless Sensor Network (WSN) Received Signal Strength Indicator (RSSI) Fingerprinting Multilateration Fusion algorithm Factor graph},
        doi={10.1007/978-3-319-66628-0_55}
    }
    
  • Wanlong Zhao
    Shuai Han
    Weixiao Meng
    Zijun Gong
    Year: 2017
    RSSI Based Positioning Fusion Algorithm in Wireless Sensor Network Using Factor Graph
    CHINACOM
    Springer
    DOI: 10.1007/978-3-319-66628-0_55
Wanlong Zhao1,*, Shuai Han1,*, Weixiao Meng1,*, Zijun Gong2,*
  • 1: Harbin Institute of Technology
  • 2: Memorial University of Newfoundland
*Contact email: zhaowanlong001@sina.cn, hanshuai@hit.edu.cn, wxmeng@hit.edu.cn, zg7454@mun.ca

Abstract

Various positioning techniques have been widely developed based on received signal strength indicator (RSSI) in Wireless Sensor Network (WSN) positioning systems. Multilateration-based positioning technique is simple and easy to realize, but it can not provide very high positioning accuracy caused by fluctuation of range measurement. Fingerprinting technique is a promising method benefitting from its high precision. However, the process of building radio map cost too much time and labor. In this paper, a fusion algorithm based on both multilateration and fingerprinting is proposed to reduce cost and maintain high accuracy at the same time. An adaptive radio propagation mode is presented in this algorithm as well as a multilateration approaches based on sparse fingerprint. Factor graph is adopted to fuse the results of these two positioning techniques. Simulation experiments demonstrate that the proposed positioning fusion algorithm performs much better than any of the original algorithms participated in the fusion process.