摘要
为了提高无线传感器节点的定位精度,针对粒子群优化算法存在的问题,提出一种改进粒子群优化算法的无线传感器网络节点定位方法。根据锚节点选择准则,把上一代和当代节点位置的平均值作为下一代目标节点的参考节点,采用改进粒子群算法对节点的定位结果进行优化,在Matlab 2012平台上进行仿真对比实验。仿真结果表明,相对于标准粒子群算法,改进粒子群算法加快了定位速度,提高了无线传感器节点定位精度,应用范围更广。
In order to improve the localization accuracy, a novel localization meothd in wireless sensor network based on improved particle swarm optimization algorithm is proposed. The average of the location of the node in the last generation and the location of the same node in the current generation is regarded as the current generation node location following with the criteria of choosing beacon nodes, and the improved particle swarm optimization algorithm is used to optimize the localization results. The simulation experiments are carried out. The results show that the proposed algorithm not only fastens the localization speed and has improved the localization accuracy effectively compared with the PSO algorithm, so it has wider application range.
出处
《计算机工程与应用》
CSCD
2014年第18期99-102,共4页
Computer Engineering and Applications
基金
周口师范学院青年科学基金重点资助项目(No.zksyqn201310B)
河南省人民政府人才培养联合基金项目(No.U1204618)
关键词
无线传感器网络
改进粒子群优化(MPSO)算法
分布式迭代平均定位
定位误差
wireless sensor networks
Modified Particle Swarm Optimization(MPSO)algorithm
distributed iterative average localization
localization error