摘要
针对DV-Hop定位算法误差大的缺点,深入分析定位误差来源后,在改进的PSO(Particle Swarm Optimization)算法的基础上提出了IDVHop-NSPSO(Improved DVHop-Neighborhood Search Particle Swarm Optimization)节点定位算法。该算法通过对三部分的改进达到DV-Hop定位精度提高的要求:(1)增设半跳细化最小跳数;(2)在计算平均跳距时引入权重系数使求得的跳距更加精确;(3)利用邻域搜索粒子群优化算法替代最小二乘法来计算未知节点的位置。仿真实验的结果表明:相较于DV-Hop算法、DV-Hop+PSO算法、模拟退火加权DV-Hop算法,IDVHop-NSPSO算法可在不显著增加计算资源的同时,明显地提高定位精度。
In view of the large error of DV-Hop positioning algorithm,after in-depth analysis of the source of positioning error,IDVHop-NSPSO algorithm based on Particle Swarm Optimization was presented on the basis of in-depth analysis of the source of positioning error of DV-Hop algorithm.The algorithm improves the precision of DV-Hop through the improvements on three parts.Firstly,half jump is added refining the minimum hop.Secondly,the weight coefficient is introduced to calculate the average jump distance to make the calculated jump distance more accurate.Thirdly,neighborhood search particle swarm optimization algorithm is used instead of least square method to calculate the location of unknown nodes.The simulation results show that compared with DV-Hop,DV-Hop+PSO and simulated annealing weighted DV-Hop algorithm,IDVHop-NSPSO algorithm can significantly improve the positioning accuracy without significantly increasing the computing resources.
作者
刘芷珺
张玲华
Liu Zhijun;Zhang Linghua(College of Communication and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210003,China;Jiangsu Engineering Research Center of Communication and Network Technology,Nanjing University of Posts and Telecommunications,Nanjing 210023,China)
出处
《电子技术应用》
2022年第9期97-102,共6页
Application of Electronic Technique
基金
国家自然科学基金(61771258)。
关键词
无线传感器网络
DV-HOP算法
粒子群优化算法
邻域搜索策略
定位精度
wireless sensor network
DV-Hop algorithm
particle swarm optimization algorithm
neighboring search strategy
location accuracy
