摘要
针对DV-Hop算法在节点随机分布的网络拓扑环境中存在较大误差的问题,提出了一种基于跳距修正粒子群优化的定位算法WPDV-Hop(weight PSO DV-Hop)。本算法通过对锚节点广播的数据分组结构进行了改进,对参考锚节点的平均每跳距离的误差进行加权处理以及用改进的粒子群(PSO)算法对定位中的迭代过程进行优化,实现WPDV-Hop定位算法的全面改进,以提高定位精度。仿真结果表明,改进的算法与原始算法相比,定位精度和算法的稳定性有明显提高。
Regarding the relatively big errors with running the DV-hop localization algorithm in a network topology scenario, with which nodes randomly distributes, a particle swarm optimization localization algorithm for WSN nodes based on modifying average hop distance was proposed. By changing the structure of data packets sent by anchor nodes with broadcasting, weighting the average hop distance error of reference anchor nodes to modify the average hop distance, and using an improved particle swarm algorithm to optimize iteration process for localization, thus, WPDV-Hop localization algorithm improvements were carried out. The simulation results indicate that the localization accuracy and the stability of the WPDV-Hop localization algorithm are significantly improved compared with the original algorithm.
出处
《通信学报》
EI
CSCD
北大核心
2013年第9期105-114,共10页
Journal on Communications
基金
国家自然科学基金资助项目(61071073)
教育部高等学校博士学科专项科研基金资助项目(20090061110043)~~
关键词
WSN
定位
误差加权
平均跳距
粒子群
wireless sensor network
localization
error-weighted
average hop distance
particle swarm algorithm
