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《Journal of Beijing University of Aeronautics and Astronautics》 2004-01
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Multiple fading Kalman filter based on hypothesis testing

Zhuang ChaowenFu LiFan Yuezu (School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China)  
A new multiple fading Kalman filtering algorithm was proposed based on hypothesis testing. The algorithm on-line modifies the noise covariance of the Kalman filter by the fading matrix using chi-square testing method so as to imp rove the accuracy and convergency of the Kalman filter when there exist errors o r when the plant was affected by unmeasurable external disturbances. The proposed algorithm was applied to a vehicle global positioning system/inerial navigation system/integrated navigation system(GPS/INS) and behaved satisfactorily.
【CateGory Index】: P228.4
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