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

作　　者：田金鹏 郑国莘 

机构地区：[1]Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Engineering, Shanghai University

出　　处：《Journal of Shanghai University(English Edition)》2011年第2期128-131,共4页上海大学学报（英文版）

基　　金：Project supported by the Shanghai Leading Academic Discipcine Project (Grant No.S30108);the National Natural Science Foundation of China (Grant No.60872021);the Science and Technology Commission of Shanghai Municipality (Grant No.08DZ2231100)

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.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.

关 键 词：wireless sensor networks （WSNs） node location localization algorithm Kalman filter （KF） 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置] TN929.5[自动化与计算机技术—控制科学与工程]