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基于最优信标组的扩展卡尔曼定位算法
引用本文:孟文超,俞立,董齐芬,王铭. 基于最优信标组的扩展卡尔曼定位算法[J]. 传感技术学报, 2011, 24(4): 581-586. DOI: 10.3969/j.issn.1004-1699.2011.04.022
作者姓名:孟文超  俞立  董齐芬  王铭
作者单位:浙江工业大学信息工程学院,杭州,310023
基金项目:浙江省教育厅重大科技攻关项目,浙江省自然科学基金项目
摘    要:节点定位是无线传感网的关键技术之一.针对传统的基于RSSI的定位算法精度低的问题,提出一种基于最优信标组的扩展卡尔曼定位算法(BBG-EKF).该算法分析影响定位精度的两个因素:未知节点与信标节点的距离和信标节点间的共线性,提出一种最优信标组选择机制,进一步通过扩展卡尔曼滤波实现精确定位.新算法复杂度低,定位过程中节点...

关 键 词:无线传感器网络  节点定位  最优信标组  扩展卡尔曼滤波

Extended Kalman Localization Algorithm Based on Best Beacon Group
MENG Wenchao,YU Li,DONG Qifen,WANG Ming. Extended Kalman Localization Algorithm Based on Best Beacon Group[J]. Journal of Transduction Technology, 2011, 24(4): 581-586. DOI: 10.3969/j.issn.1004-1699.2011.04.022
Authors:MENG Wenchao  YU Li  DONG Qifen  WANG Ming
Affiliation:(College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China)
Abstract:Node localization is one of the fundamental issues in wireless sensor networks.In order to solve the problem of low location accuracy in traditional RSSI-Based algorithm,a novel localization algorithm based on the best beacon group and extended Kalman filter(BBG-EKF)is proposed.Firstly,two factors which influence the location accuracy are analyzed.These two factors are the distance between beacons and unknown nodes,and,the colinearity of beacons.Then a new selection scheme for the best beacon group is proposed.Finally,the extended kalman filter method is applied to estimate the positions of unknown nodes.The proposed algorithm has the advantage of low complexity and low communication overhead.The simulation illustrates that the proposed scheme keeps high location accuracy under different communication radius and beacon density.Therefore,it meets the needs for the most positioning system in wireless sensor networks.
Keywords:wireless sensor networks  node localization  best beacon group  extended Kalman filter
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