基于RSSI 和分步粒子群算法的无线传感器网络定位算法
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太原理工大学计算机科学与技术学院,太原030024.

作者简介:

冯秀芳

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TP393

基金项目:

山西省科技基础条件平台建设项目(20110910003-0103).


Wireless sensor networks locating algorithm based on RSSI and split-step particle swarm optimization algorithm
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Department of Computer Science and Technology,Taiyuan University of Technology,Taiyuan 030024,China.

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    摘要:

    为了更加合理地分配网络资源、采集性能优良的信息来更好地完成任务, 提高事件的定位精确度, 提出一种基于接收信号强度指示(RSSI) 和分步粒子群算法的无线传感器网络定位算法(IPSO-IRSSI). 该算法在分析RSSI 无线传播损耗模型的基础上, 结合优胜劣汰的选择思想以及目标函数最优的权重自适应方法, 提出过滤锚节点机制和粒子群分步算法. 仿真实验结果表明, 该算法具有较高的定位精度, 优于距离相关的传统定位算法.

    Abstract:

    In order to distribute net resource reasonably and gather better performed information to fulfill tasks and improve the locating accuracy of events, a wireless sensor network locating algorithm, called improved particle swarm optimizationimproved received signal strength indicator(IPSO-IRSSI), based on relative received signal strength(RSSI) and the split-step particle swarm optimization algorithm is proposed. Based on the analysis of RSSI radio propagation loss model, combined with the idea of survival of the fittest selection and adaptive weight approach of the optimal objective function the proposed algorithm, promotes a mechanism of filtration of anchor nodes and a particle swarm optimization step algorithm. Simulation experiments dates show that the algorithm obtains a better locating accuracy and is superior to the distance related traditional locating algorithm.

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引用本文

冯秀芳 吕淑芳.基于RSSI 和分步粒子群算法的无线传感器网络定位算法[J].控制与决策,2014,29(11):1966-1972

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  • 收稿日期:2013-07-10
  • 最后修改日期:2014-01-09
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  • 在线发布日期: 2014-11-20
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