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

Research paper by Jin-peng Tian, Guo-xin Zheng

Indexed on: 16 Apr '11Published on: 16 Apr '11Published in: Journal of Shanghai University (English Edition)



Abstract

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.