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Communications and Networking. 15th EAI International Conference, ChinaCom 2020, Shanghai, China, November 20-21, 2020, Proceedings

Research Article

An Improved HMFCW Algorithm for Ranging in RFID System

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  • @INPROCEEDINGS{10.1007/978-3-030-67720-6_49,
        author={Zengshan Tian and Shuwen Wu and Liangbo Xie and Xixi Liu},
        title={An Improved HMFCW Algorithm for Ranging in RFID System},
        proceedings={Communications and Networking. 15th EAI International Conference, ChinaCom 2020, Shanghai, China, November 20-21, 2020,  Proceedings},
        proceedings_a={CHINACOM},
        year={2021},
        month={2},
        keywords={Phase cycle ambiguity Improved HMFCW algorithm The point with large phase error Phase error tolerance Ranging},
        doi={10.1007/978-3-030-67720-6_49}
    }
    
  • Zengshan Tian
    Shuwen Wu
    Liangbo Xie
    Xixi Liu
    Year: 2021
    An Improved HMFCW Algorithm for Ranging in RFID System
    CHINACOM
    Springer
    DOI: 10.1007/978-3-030-67720-6_49
Zengshan Tian1, Shuwen Wu1,*, Liangbo Xie1, Xixi Liu1
  • 1: School of Communication and Information Engineering
*Contact email: 1014295949@qq.com

Abstract

Since the measured phase is usually a wrapped phase during ranging, the phase-based ranging method needs to solve the ambiguity so as to obtain the true phase. HMFCW (heuristic multi-frequency continuous wave) algorithm provides the same tolerance of error for the observed phase of different frequencies. When the error of phase is within the tolerance and the range of ranging is less than the period, the phase error tolerance method can get the correct cycle number, and achieve a ranging accuracy of centimeter. However, when phase errors of some frequencies are large, HMFCW algorithm may have difficulty in solving the integer ambiguity, which leads to the decrease of ranging accuracy. In this paper, an improved HMFCW algorithm based on HMFCW algorithm is proposed. The improved HMFCW algorithm calculates the average value of the clustering phase results to eliminate the phases with large errors, and performs the cycle calculation to obtain the ranging value. Simulation results show that improved HMFCW algorithm can solve the problem of error in the cycle ambiguity solution caused by the point with large phase error effectively, and improve the ranging accuracy.

Keywords
Phase cycle ambiguity Improved HMFCW algorithm The point with large phase error Phase error tolerance Ranging
Published
2021-02-02
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-67720-6_49
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