基于差异演化粒子群的WSN无需测距DV-Hop定位算法  

Research on DV-Hop Location Algorithm for WSN Without Ranging Based on Differential Evolution Particle Swarm

作　　者：解姗姗[1] 曾健民[1] XIE Shan-shan;ZENG Jian-min(School of Information Management,Minnan University of Science and Technology,Shishi 362700,China)

机构地区：[1]闽南理工学院信息管理学院,福建石狮362700

出　　处：《三明学院学报》2018年第6期6-12,共7页Journal of Sanming University

基　　金：福建省中青年教师教育科研项目(JT180690);福建省教育厅应用型转变试点项目(闽教高[2016]16号)

摘　　要：针对DV-Hop算法存在定位精度的问题,提出了一种基于差异演化粒子群的无线传感网络DV-Hop节点定位算法。首先通过引入差异演化计算的变异、交叉及选择过程,对传统粒子群优化算法进行了改进,维持了种群的多样性,从而提高了算法的全局搜索能力。然后,采用改进的粒子群优化算法对DV-Hop进行了优化计算并给出了具体流程。仿真实验结果显示,与传统DV-Hop算法和某些现有的改进算法,相比提出的改进DV-Hop定位算法具有较小的定位误差,有效提升了网络中节点定位的精度。Aiming at the problem of location accuracy of DV-Hop algorithm,a DV-Hop node localization algorithm based on differential evolution particle swarm optimization for wireless sensor networks is proposed.Firstly,by introducing the mutation,intersection and selection process of differential evolution calculation,the traditional particle swarm optimization algorithm is improved,and the diversity of the population is maintained,thus improving the global search ability of the algorithm.Then,the improved particle swarm optimization algorithm is used to optimize the DV-Hop and the specific process is given.The simulation results show that compared with the traditional DV-Hop algorithm and some existing improved algorithms,the improved DV-Hop positioning algorithm has smaller positioning error and effectively improves the accuracy of node positioning in the network.

关 键 词：节点定位 无线传感器网络 粒子群优化 DV-HOP 定位精度 差异演化 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置]