Journal of Jilin University Science Edition ›› 2022, Vol. 60 ›› Issue (3): 713-720.

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Location Algorithm Based on Gaussian Mixture Model in Wireless Sensor Network

FANG Xing1, LUO Yin2,3, CAO Jia2,3, XU Nan2,3, JIANG Shuibin2,3, HAO Yanni2,3   

  1. 1. School of Economics and Management, Tianjin University, Tianjin 300072, China; 2. Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; 3. Beijing Wenge Technology Co., Ltd., Beijing 100000, China
  • Received:2021-06-03 Online:2022-05-26 Published:2022-05-26

Abstract: Aiming at  the influence of distance error on the location results, we proposed a location algorithm based on Gaussian mixture model  (GMM) in wireless sensor network (WSN). In this algorithm, the GMM  method was introduced into the location problem of WSN. The  distance information with large error was found by using the analysis of GMM and eliminated. The remaining distance information was solved by  trilateral measurement location method, and the position was  estimated combined with wighted location algorithm. Simulation results show  that the improved  algorithm can improve positioning accuracy and the positioning  results are  more stable.

Key words: Gaussian mixture model (GMM), wireless sensor networks (WSNs), location

CLC Number: 

  • TP391