传感技术学报2016，Vol.29Issue(9)：1410-1415,6.DOI:10.3969/j.issn.1004-1699.2016.09.020
基于跳距与改进粒子群算法的DV-Hop定位算法
DV-Hop Localization Algorithm Based on Hop-Size and Improvement Particle Swarm Optimization
摘要
Abstract
In order to solve DV-Hop low localization accuracy,a novel localization method based on modified weighted average hop-size and improved particle swarm optimization algorithm is proposed. On the one hand, weighted average both hop-size error and estimated distance error modify initial average hop-size. On the other hand,index and logarithmic decrement of piecewise function improve inertia weight of PSO. Furthermore,combin⁃ing with localization update of Atificial Fish Swarm Algorithm improve PSO’s localization update. Then,improved algorithm estimate unknown node coordination. The experiment shows localization accuracy and stability of the method is greatly improved.关键词
无线传感器网络/Distance Vector-Hop Algorithm/改进的粒子群算法/平均每跳距离Key words
wireless sensors networks(WSN)/DV-Hop Algorithm/improved particle swarm optimization algorithm (PSO)average hop-size分类
信息技术与安全科学引用本文复制引用
范时平,罗丹,刘艳林..基于跳距与改进粒子群算法的DV-Hop定位算法[J].传感技术学报,2016,29(9):1410-1415,6.基金项目
基于物联网技术的呼吸、脉搏异变及跌落的实时监测与报警的关键技术研究项目 （）
