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J4 ›› 2013, Vol. 48 ›› Issue (05): 78-82.

• 前沿进展 • 上一篇    下一篇

基于微粒群优化的三维无线传感网定位算法研究

吕家亮1,2,3,王英龙1,3,崔焕庆1,魏诺2,3,郭强2,3   

  1. 1. 山东科技大学信息科学与工程学院,山东 青岛 266590; 2. 山东省计算中心,山东 济南 250014;
    3. 山东省计算机网络重点实验室,山东 济南 250014
  • 收稿日期:2012-10-19 出版日期:2013-05-20 发布日期:2013-05-10
  • 作者简介:吕家亮(1982- ),男,博士研究生,助理研究员,主要研究领域为无线传感器网络.Email:lvjl@sdas.org
  • 基金资助:

    国家自然科学基金资助项目(61272433);山东省自然科学基金资助项目(ZR2009GQ002, ZR2010FQ014)

Study on the node localization schemes of three dimensional wireless sensor networks based on particle swarm optimization

L Jia-liang1,2,3, WANG Ying-long1,3, CUI Huan-qing1,  WEI Nuo2,3, GUO Qiang2,3   

  1. 1. College of Information Science and Engineering, Shandong University of Science and Technology,
    Qingdao 266590, Shandong, China;
    2. Shandong Computer Science Center, Jinan 250014, Shandong, China;
    3. Shandong Provincial Key Laboratory of Computer Network, Jinan 250014, Shandong, China
  • Received:2012-10-19 Online:2013-05-20 Published:2013-05-10

摘要:

为解决三维空间下无线传感器网络节点的精确定位问题,提出了一种三维空间微粒群搜索算法(3DPSO),将节点定位用优化问题进行描述。为了提高算法的执行效率和定位精度,提出了一种基于距离的目标函数来评价微粒的适应度。对微粒的搜索空间进行了限制,以加快定位结果的收敛速度。在理想环境和有测距误差的情况下证明了该算法的可行性和有效性。仿真结果表明,与典型的定位算法相比,该算法具有更好的健壮性和更高的定位精度。

关键词: 无线传感器网络;节点定位;锚节点;微粒群优化算法

Abstract:

To solve the accurate localization of three-dimensional wireless sensor networks, a three-dimensional localization algorithm based on particle swarm optimization (3DPSO) was presented. In order to improve the efficiency and precision of localization method, a distancebased objective function to evaluate the fitness of particles was presented. Besides, in order to speed up the convergence rate of the localization result, the search space of the particles was limited. Finally, in the case of the ideal and ranging error environment, the feasibility and effectiveness of the algorithm was proved. Compared to the typical schemes, Simulation results reveal that this algorithm provides better robustness and high positioning accuracy.

Key words:  wireless sensor networks (WSNs); node localization; anchor node; particle swarm optimization (PSO) algorithm

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