传感技术学报2016，Vol.29Issue(4)：572-577,6.DOI:10.3969/j.issn.1004-1699.2016.04.018
结合极大似然距离估计的MDS-MAP节点定位算法
Localization Algorithm for Wireless Sensor Networks Based on MDS-MAP Integrated with Maximum Likelihood Estimating
摘要
Abstract
The multidimensional scaling(MDS)positioning algorithms of wireless sensor networks usually use the length of shortest path in lieu of the Euclidean distance between two nodes to build the distance matrix,which may result in large positioning errors,especially when the network topology is irregular. To solve this problem,a new lo⁃calization algorithm MDS-MAP(MLE)was proposed in this work,in which the MDS-MAP method and Maximum Likelihood Estimating was combined.The information coming from the 1-hop neighbors are deemed as the input of the maximum likelihood method to estimate the relative coordinate of the tested node. And this process will iterate until all unknown nodes’relative coordinate are estimated. And then the global map can be transformed to an abso⁃lute map based on the absolute positions of anchors. Simulation results shows that the MDS-MAP(MLE)algorithm can get high positioning precision,either for regular or irregular network. In addition,the positioning errors can stay relatively constant at a low level when the network connectivity vary within a certain range.关键词
无线传感网络/定位算法/多维定标/极大似然方法Key words
wireless sensor networks/localization algorithm/multidimensional scaling/maximum likelihood 6210Q分类
信息技术与安全科学引用本文复制引用
李津蓉,王万良,介婧,姚信威..结合极大似然距离估计的MDS-MAP节点定位算法[J].传感技术学报,2016,29(4):572-577,6.基金项目
国家自然科学基金项目（61379123）；国家自然科学基金项目（61402414）；浙江省自然科学基金项目 （）
