一种考虑可能区域和智能搜索相结合的定位算法  

A new method for localization based on network coverage and intelligent search

作　　者：周书旺[1,2,3] 王英龙[1,3] 郭强[1,2] 魏诺[1,2] 郭文娟[1,3] 

机构地区：[1]山东省计算中心,山东济南250014 [2]山东省计算机网络重点实验室,山东济南250014 [3]山东师范大学信息科学与工程学院,山东济南250014

出　　处：《山东大学学报（理学版）》2010年第11期27-31,共5页Journal of Shandong University(Natural Science)

基　　金：国家自然科学基金资助项目(60802030);山东省中青年科学家科研奖励基金资助项目(2007BSC01002);山东省科技攻关计划项目(2007GG2QT01007)

摘　　要：提出了一种考虑可能区域和智能搜索相结合的无线传感器网络节点定位算法。该算法首先利用各个锚节点到未知节点的距离确定未知节点的可能区域,然后利用微粒群算法(particle swarm optimization,PSO)搜索出落在可能区域内的符合条件的结果,最后取符合条件的结果的均值作为未知节点的估计位置。实验结果表明,该算法定位精度较高,并且具有很强的鲁棒性,相比于一般的定位算法(如最小二乘法),在测距误差为35%的情况下,其定位精度可以提高49%左右。A new method for localization based on network coverage and intelligent search （CIL） was presented, First, the distance from each anchor nodes to the unknown node was used to determine the possible region. Second, the positions which meet specific criteria were searched out by a particle swarm optimization algorithm, and the searching results within the possible region were recorded. Finally, the unknown node＇s localization could be obtained by calculating the average recording results. Experimental results showed that CIL has high positioning accuracy and strong robustness. Compared with normal schemes such as the least square method （LS）, the CIL＇s positioning accuracy could improve 49% when the ranging error was 35%.

关 键 词：无线传感器网络 节点定位 微粒群算法 可能区域 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]