Real-time localization estimator of mobile node in wireless sensor networks based on extended Kalman filter

被引：0
|
作者：
田金鹏 [1 ]
郑国莘 [1 ]
机构：
[1] Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Engineering, Shanghai University
来源：
Advances in Manufacturing | 2011年 / 02期
基金：
中国国家自然科学基金;
关键词：
wireless sensor networks (WSNs); node location; localization algorithm; Kalman filter (KF);
D O I：
暂无
中图分类号：
TP212.9 [传感器的应用]; TN929.5 [移动通信];
学科分类号：
080202 ; 080402 ; 080904 ; 0810 ; 081001 ;
摘要：
Localization of the sensor nodes is a key supporting technology in wireless sensor networks (WSNs). In this paper, a real-time localization estimator of mobile node in WSNs based on extended Kalman filter (KF) is proposed. Mobile node movement model is analyzed and online sequential iterative method is used to compute location result. The detailed steps of mobile sensor node self-localization adopting extended Kalman filter (EKF) is designed. The simulation results show that the accuracy of the localization estimator scheme designed is better than those of maximum likelihood estimation (MLE) and traditional KF algorithm.
引用
收藏
页码：128 / 131
页数：4
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