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Adaptive Kalman filter combined with prediction and fault tolerance for target tracking


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Adaptive Kalman filter combined with prediction and fault tolerance for target tracking
Dai Hongde12Zou Jie2Xu Shenghong1Wang Yongting2 Wu Xiaonan1Wu Guangbin1
1.Department of Control Engineering,Naval Aeronautical and Astronautical University,Yantai 264001,China; 2.Science and Technology on Electron-optic Control Laboratory,Luoyang 471009,China
target tracking Kalman filter adaptive prediction estimation fault tolerant anti-interference on-line matching innovation covariance
An adaptive Kalman filter,based on the online matching of innovation covariance,is presented to overcome the problem of accuracy degrade or even divergence when there exists tremendous modeling errors and to improve the accuracy of target tracking.The area where the target may appear at the next epoch is predicted by one-step Kalman predictor,based the position of the target estimated by Kalman filter at present to avoide searching the whole image to find the target and to reduce the calculation burden.Abnormal measurement detection is also studied and the abnormal measurements are replaced by the Kaman predicted measurement,to avoid the disturbance caused by the abnormal measurement and to increase the anti-interference ability.Experimental results show that the accuracy and robustness of target tracking can be improved by the algorithm presented here.


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Last Update: 2015-02-28