吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

粒子群算法修正测距的无线传感器网络节点定位

楼国红, 张剑平   

  1. 太原工业学院 电子工程系, 太原 030008
  • 收稿日期:2017-01-23 出版日期:2018-05-26 发布日期:2018-05-18
  • 通讯作者: 楼国红 E-mail:956084527@qq.com

Ranging Distance Modified by Particle Swarm Algorithm for WSN Node Localization

LOU Guohong, ZHANG Jianping   

  1. Department of Electronic Engineering, Taiyuan Institute of Technology, Taiyuan 030008, China
  • Received:2017-01-23 Online:2018-05-26 Published:2018-05-18
  • Contact: LOU Guohong E-mail:956084527@qq.com

摘要: 为获得理想的节点定位结果, 设计一种基于粒子群修正测距的无线传感器节点定位算法. 首先对经典无线传感器节点定位算法DV-Hop的工作原理进行分析, 找到导致测距误差的因素; 然后用粒子群算法对无线传感器节点之间的测距进行修正, 以减少节点间的测距误差, 并对标准粒子群算法的不足进行相应的改进; 最后通过仿真实验与当前经典无线传感器节点定位算法进行对比测试. 测试结果表明, 在相同工作环境下, 该算法提高了无线传感器节点的定位精度, 且未增加额外硬件开销.

关键词: 无线传感器网络, 跳距修正, 粒子群优化算法, 估计误差, 定位精度

Abstract: In order to obtain ideal result of node localization, we designed a wireless sensor node localization algorithm based on ranging distance modified by particle swarm. First, the working principle of the classical wireless sensor node localization algorithm (DVHop) was analyzed to find the factors that lead to the ranging distance error, and then, particle swarm optimization algorithm was used to modify the ranging distance between the nodes of wireless sensor to reduce ranging distance error among the nodes in which standard particle swarm optimization algorithm was improved correspondingly. Finally, the simulation experiments were compared with the classical node localization algorithms of wireless sensor. The test results show that, in the same working environment, the proposed algorithm improves the location precision of wireless sensor nodes, and does not increase the extra hardware overhead.

Key words: location precision, particle swarm optimization (PSO) algorithm, wireless sensor network, estimation error, hop distance correction

中图分类号: 

  • TP393