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  2007, Vol. 20 Issue (6): 849-854    DOI:
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UKF Algorithm Based on MEstimators and Its Application in Motion Estimation
ZHOU LuPing1, WANG ZhiLing1, CHEN ZongHai1,2
1.MDEMS Key Laboratory of Multimedia Calculation and Communication, Department of Automation, University of Science and Technology of China, Hefei, 230027
2.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080

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Abstract  To solve the problems on nonlinear of motion model and robustness of motion estimation, a robust unscented kalman filter (UKF) method called MUKF is proposed, which is combined with the principle of the equivalent weight of Mestimate. In this method, the UKF is used to get the initial estimation of the parameters of motion. Then more accurate estimations are obtained by MUKE. The combination of Mestimators and UKF not only solves the nonlinear problems but also conquers the inflation of outliers, which has greatly improved the robustness of estimation. Finally, experimental results demonstrate the validity of the proposed method.
Key wordsMotion Estimation      Kalman Filter,Unscented Kalman Filter      MEstimators      Robust Estimation     
Received: 13 June 2006     
ZTFLH: TP391  
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ZHOU LuPing
WANG ZhiLing
CHEN ZongHai
Cite this article:   
ZHOU LuPing,WANG ZhiLing,CHEN ZongHai. UKF Algorithm Based on MEstimators and Its Application in Motion Estimation[J]. , 2007, 20(6): 849-854.
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