吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (4): 1191-1196.doi: 10.13229/j.cnki.jdxbgxb201404044

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Self-adaptive Monte Carlo localization algorithm of mobile nodes in WSN

LI Jian-po, SHI Ming, ZHONG Xin-xin   

  1. School of Information Engineering, Northeast Dianli University, Jilin 132012, China
  • Received:2013-01-30 Online:2014-07-01 Published:2014-07-01

Abstract: To overcome the disadvantages of low localization accuracy and poor efficiency of Monte Carlo Localization (MCL) algorithm in harsh Wireless Sensor Network (WSN), a self-adaptive localization algorithm based on MCL is proposed. The sample particles in different regions have different effects on unknown node localization accuracy. The proposed algorithm assigns self-adaptive weights to sample particles in different regions to position the unknown nodes. At the same time, the algorithm adds the constraint condition using the last-time sample particles. Simulation results show that the average localization error of the proposed self-adaptive MCL algorithm descends 13% at different degrees of irregularity. The average localization error descends about 10% at different node speeds. The network coverage rate reaches 99.19%.

Key words: communication, mobile node localization, Monte Carlo localization(MCL) algorithm, wireless sensor network

CLC Number: 

  • TN911
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