International Workshop on Millimeter-wave Radar Technology and Application

Research Article

Fast Fingerprint Database Construction Method in Bluetooth Indoor Positioning System

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  • @INPROCEEDINGS{10.4108/eai.21-6-2018.2276621,
        author={Mu Zhou and Xiaoxiao Jin and Lingxia Li and Zengshan Tian and Haoliang Ren and Haifeng Cong},
        title={Fast Fingerprint Database Construction Method in Bluetooth Indoor Positioning System},
        proceedings={International Workshop on Millimeter-wave Radar Technology and Application},
        publisher={EAI},
        proceedings_a={IWMRTA},
        year={2018},
        month={9},
        keywords={indoor positioning; radial basis function; fingerprint database construction; pdr; bluetooth},
        doi={10.4108/eai.21-6-2018.2276621}
    }
    
  • Mu Zhou
    Xiaoxiao Jin
    Lingxia Li
    Zengshan Tian
    Haoliang Ren
    Haifeng Cong
    Year: 2018
    Fast Fingerprint Database Construction Method in Bluetooth Indoor Positioning System
    IWMRTA
    EAI
    DOI: 10.4108/eai.21-6-2018.2276621
Mu Zhou1, Xiaoxiao Jin1,*, Lingxia Li1, Zengshan Tian1, Haoliang Ren1, Haifeng Cong1
  • 1: Chongqing University of Posts and Telecommunications
*Contact email: jinxiaoxiaosx@163.com

Abstract

The fingerprint samples are collected point-by-point in traditional fingerprint database construction approach, which is inefficient. In response to this problem, this paper proposes a database construction system based on fast acquisition of fingerprint samples and the Radial Basis Function (RBF). Firstly, several linear paths are marked in the indoor environment according to the determined sampling interval and sampling number. Secondly, according to the Pedestrian Dead Reckoning (PDR) algorithm, the coordinates are assigned to the Received Signal Strength (RSS) to form a sparse fingerprint database. Thirdly, we select the RBF to extend sparse fingerprint database, with the purpose of constructing a database with higher fingerprint granularity. Experimental results show that our proposed approach can be applied to reduce the labor cost in database construction, as well as guaranteeing high-enough accuracy performance of fingerprint database.