基于M估计的UKF算法及其在运动估计中的应用

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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 words： Motion Estimation Kalman Filter,Unscented Kalman Filter MEstimators Robust Estimation

Received: 13 June 2006

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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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http://manu46.magtech.com.cn/Jweb_prai/EN/ OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2007/V20/I6/849

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