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基于RSSI的极大似然与加权质心混合定位算法
引用本文:韩江洪,祝满拳,马学森,刘会平. 基于RSSI的极大似然与加权质心混合定位算法[J]. 电子测量与仪器学报, 2013, 0(10): 937-943
作者姓名:韩江洪  祝满拳  马学森  刘会平
作者单位:[1]合肥工业大学计算机与信息学院,合肥230009 [2]安全关键工业测控技术教育部工程研究中心,合肥230009
基金项目:教育部博士点基金(20100111110004)、广东省教育部产学研结合(2011B090400524)、安徽省高校省级自然科学研究项目(KJ2011ZD01,KJ2012A233)
摘    要:随着无线传感器网络的发展,日益需要更加精确的位置信息来支撑其相关的应用.通过分析待定位节点定位过程中产生的误差,对二阶段定位算法、接收信号强度指示(received signal strength indicator,RSSI)定位技术和质心算法进行深入的研究,提出了极大似然与加权质心混合定位算法:首先通过极大似然估计法对待定位节点进行粗略估计,然后利用加权质心算法对待定位节点坐标估计求精,进一步提高定位精度.仿真实验结果表明,该算法能够在定位精度方面有较大的提高.

关 键 词:无线传感器网络  定位  接收信号强度指示  极大似然估计  质心算法

Hybrid localization algorithm of maximum likelihood and weighted centroid based on RSSI
Han Jianghong,Zhu Manquan,Ma Xuesen,Liu Huiping. Hybrid localization algorithm of maximum likelihood and weighted centroid based on RSSI[J]. Journal of Electronic Measurement and Instrument, 2013, 0(10): 937-943
Authors:Han Jianghong  Zhu Manquan  Ma Xuesen  Liu Huiping
Affiliation:1. School of Computer and Information, Hefei University of Technology, Hefei 230009, China ; 2. Engineering Research Center of Safety Critical Industry Measurement and Control Technology, Ministry of Education, Hefei 230009, China)
Abstract:With the development of wireless sensor networks, it growingly needs more precise location information to support its application. The paper proposes the hybrid localization algorithm using least squares method with the weighted centroid based on the analysis of the error produced when unknown node is located, and the study of the two-phase positioning algorithm RSSI (received signal strength indicator) location technology and centroid algo- rithm. Firstly the paper estimates roughly the unknown node' s coordinate by using the maximum likelihood estima- tion, then refines the coordinate of unknown node by using the weighted centroid algorithm. The simulation results show that the algorithm can greatly improve the localization accuracy.
Keywords:localization  RSSI  maximum likelihood estimation  centroid algorithm
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