计算机应用研究2017，Vol.34Issue(12)：3775-3778,3783,5.DOI:10.3969/j.issn.1001-3695.2017.12.058
基于最优跳距和改进粒子群的DV-Hop定位算法
DV-Hop localization algorithm based on best average hop distances and improved particle swarm
摘要
Abstract
The DV-Hop localization algorithm,which uses the product of the hop count and the average hop distance to estimate distance and uses the maximum likelihood estimation method for positioning,has larger error.Aiming at the problem above,this paper proposed a developed localization algorithm OPDV-Hop,which based on the optimal hop distance and the improved particle swarm.Firstly,this algorithm adopted communication radius to revise hops between nodes.Then it optimized the current hop distance according to the average hop distance in the adjacent area of unknown nodes.Lastly,it applied the improved particle swarm algorithm to optimize the unknown node coordinates.The simulation results show that,compared with the DV-Hop algorithm,the DV-Hop algorithm based on particle swarm and the algorithm based on improved particle swarm,OPDV-Hop algorithm reduces the errors by about 18％,13％ and 7％ respectively.Thus,it can effectively lower down the estimation errors and improve the positioning accuracy.关键词
无线传感器网络/DV-Hop算法/跳数修正/最优跳距/粒子群算法Key words
wireless sensor network/DV-Hop algorithm/corrected hop/optimal hop distances/particle swarm algorithm分类
信息技术与安全科学引用本文复制引用
李新春,郭欣欣..基于最优跳距和改进粒子群的DV-Hop定位算法[J].计算机应用研究,2017,34(12):3775-3778,3783,5.基金项目
国家自然科学基金资助项目(61372058) （61372058）
