A Robust Vector Matching Localization Approach Based on Multiple Channels SSD Fingerprinting of Zigbee Networks

نویسندگان

  • Xiansheng Guo
  • Lei Chu
  • Baocang Li
  • Baogen Xu
  • Qun Wan
  • Yijiang Shen
چکیده

We present a robust multiple-channel vector-matching localization approach (MCVM) based on signal strength difference (SSD) fingerprinting of ZigBee Network. Compared with some existing algorithms, our presented approach has threefold advantages: firstly, far fewer numbers of received signal strength (RSS) measurements and reference nodes are needed; secondly, it shows more robustness to the fluctuation of RSS; thirdly, it requires low time-consuming signal strength collection surveys in the location space. We demonstrate the performances of our algorithm experimentally using different numbers of channels, reference nodes and training points. The Cramér-Rao Low Bound (CRLB) of SSD is derived in order to compare the performance of the different localization methods addressed. The experimental results show the efficacy of our proposed approach.

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تاریخ انتشار 2014