UKF Algorithm Based on MEstimators and Its Application in Motion Estimation
ZHOU LuPing1, WANG ZhiLing1, CHEN ZongHai1,2
1.MDEMS 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
Abstract：To solve the problems on nonlinear of motion model and robustness of motion estimation, a robust unscented kalman filter (UKF) method called MUKF is proposed, which is combined with the principle of the equivalent weight of Mestimate. In this method, the UKF is used to get the initial estimation of the parameters of motion. Then more accurate estimations are obtained by MUKE. The combination of Mestimators 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.
周露平，王智灵，陈宗海. 基于M估计的UKF算法及其在运动估计中的应用[J]. 模式识别与人工智能, 2007, 20(6): 849-854.
ZHOU LuPing , WANG ZhiLing , CHEN ZongHai. UKF Algorithm Based on MEstimators and Its Application in Motion Estimation. , 2007, 20(6): 849-854.
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2007, Vol. 20 
