Computer Science ›› 2020, Vol. 47 ›› Issue (9): 252-257.doi: 10.11896/jsjkx.200400038

Special Issue: Internet of Things

• Computer Network • Previous Articles     Next Articles

RFID Indoor Relative Position Positioning Algorithm Based on ARIMA Model

XU He1,2, WU Man-xing1, LI Peng1,2   

  1. 1 School of Computer Science,Nanjing University of Posts and Telecommunications,Nanjing 210023,China
    2 Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks,Nanjing 210003,China
  • Received:2020-04-08 Published:2020-09-10
  • About author:XU He,born in 1985,associate professor,master supervisor,is a member of China Computer Federation.His main research interests include Internet of Things (IoT) technology and applications.
    LI Peng,born in 1979,Ph.D,professor,master supervisor,is a member of China Computer Federation.His main research interests include computer communication networks,cloud computing,and information security.
  • Supported by:
    National Key R&D Program of China (2019YFB2103003,2018YFB1003201),National Natural Science Foundation of China (61672296,61602261,61872196,61872194,61902196), Scientific and Technological Support Project of Jiangsu Province (BE2017166,BE2019740),Major Natural Science Research Projects in Colleges and Universities of Jiangsu Province (18KJA520008),Six Talent Peaks Project of Jiangsu Province (RJFW-111).

Abstract: For indoor positioning scenarios,there is often a need to obtain the order in which certain items are placed.RFID(Radio Frequency Identification) is one of the solutions that can be selected because of its light weight and low cost.To solve the problem of relative positioning of items by studying the ARIMA based on the phase and time series prediction model,this paper proposes an indoor relative position positioning algorithm based on UHF (Ultra-High Frequency) RFID tags.By using passive RFID tags and readers,moving the RFID antenna to obtain the phase value,the ARIMA model is used to predict the sequence of the phase change during the movement of the antenna,the time series is predicted to reach a certain time stamp,and then the prediction time is given.The weights are assigned to the time stamps of some special phase points in the process of stamping and phase change,and the final time stamps are obtained to sort relative positions.Experiments show that this RFID indoor relative position positioning system can achieve recognition accuracy rateby 96.67% for book sequence detection in a library environment.Compared with the classical STPP algorithm and HMRL algorithm,its performance is greatly improved.

Key words: ARIMA Model, Indoor positioning, Phase, Relative position, RFID

CLC Number: 

  • TP301.6
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