无线传感器网络三维定位交叉粒子群算法  

Three-dimensional Localization Method of Agriculture Wireless Sensor Networks Based on Crossover Particle Swarm Optimization

作　　者：王俊[1] 李树强[1] 刘刚[2] 

机构地区：[1]河南科技大学农业工程学院,洛阳471003 [2]中国农业大学现代精细农业系统集成研究教育部重点实验室,北京100083

出　　处：《农业机械学报》2014年第5期233-238,215,共7页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家高技术研究发展计划(863计划)资助项目(2011AA100704)

摘　　要：针对标准粒子群算法进化后期收敛速度慢、易陷入局部极小点、早熟收敛等问题,提出一种基于交叉粒子群的农业无线传感器网络三维定位算法。该方法主要包括汇聚节点选取、测量距离修正、节点定位3个阶段,通过借鉴遗传算法交叉操作的思想,增加粒子的多样性,减小测距误差、锚节点数量对定位结果的影响,有效提高定位算法全局搜索能力。仿真结果表明,该方法的稳定性和定位精度均优于标准粒子群算法。在测距误差和锚节点数量相同的条件下,与混合蛙跳定位算法进行性能比较,两种算法的最大定位误差分别为1.337 8 m、1.747 3 m,最小定位误差分别为0.258 3 m、0.561 5 m,平均定位误差分别为0.651 2 m、1.044 7 m。For the standard particle swarm optimization algorithm is easy to appear slow convergence speed, emerge premature convergence and fall into local minimum point in the later evolution, a kind of localization algorithm based on cross particle swarm optimization for wireless sensor networks was presented to solve these problems. The approach mainly included three stages： sink node selection, measure distances amendment and unknown sensor node localization. By referring to the crossover operation of genetic algorithm idea, cross particle swarm optimization algorithm could increase the diversity of particles and reduce the distance measure error and the influence of anchor node number on localization result. The simulation experiment result showed that the stability and localization accuracy of the method proposed are better than those of the standard particle swarm optimization algorithm. Under the condition of same measure error and the equal number of anchor nodes, the new method was compared with the shuffled frog leaping algorithm. And the compared results are as follows： the maximum of localization errors are 1.3378m and 1.7473m, respectively; the minimum of localization errors are 0.2583 m and 0.5615m, respectively; the average localization errors are 0.6512m and 10447m, respectively. Results indicate that the method proposed is suitable for agriculture wireless sensor network localization.

关 键 词：无线传感器网络 定位 交叉粒子群算法 测量距离修正 

分 类 号：TP393.17[自动化与计算机技术—计算机应用技术]