摘要
针对无线传感器网络(WSNs)无标识节点的定位问题,引入移动锚节点收集节点的接收信号强度(RSS)数据序列,利用无监督的聚类算法分析数据确定节点个数,依据锚节点运行的不同驻点,提取最强RSS信号进行圆环交叉搜索并标识覆盖网格重叠区域,再利用极大值(EM)算法筛选出可能含有未知节点的区域,最后用改进的粒子群优化(PSO)算法最终确定符合聚类个数的最优未知节点坐标。实验仿真结果表明:该算法在未知节点稀疏分布情况下,可以准确地估算未知节点个数和位置坐标。
Aiming at localization problem of nodes without identification in wireless sensor networks（ WSNs）,introduce received signal strength（ RSS） data sequence which gathered by mobile anchor node,use unsupervised clustering algorithm to determine the number of unknown nodes,and extract the strongest RSS signal achieved by anchor node at different stationary point,to carry out ring crossing search for identifying the grid overlapping area.Then,pick out the area which may contain unknown nodes by using the maximum value algorithm. Finally,the improved particle swarm optimization（ PSO） algorithm determines the unknown nodes ＇ coordinates which is most consistent with the number of clusters. Simulation results show that the algorithm can accurately estimates the number and localization of unknown nodes in the sparse environment.
出处
《传感器与微系统》
CSCD
2016年第12期52-54,59,共4页
Transducer and Microsystem Technologies
基金
江苏省六大人才高峰基金资助项目(2012-WLW-006)
关键词
聚类算法
接收信号强度
圆环
粒子群优化算法
clustering algorithm
received signal strength（RSS）
ring
particle swarm optimization（PSO） algorithm
