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基于HuberM估计的鲁棒Cubature卡尔曼滤波算法

DOI: 10.13195/j.kzyjc.2012.1565, PP. 572-576

Keywords: Cubature,卡尔曼滤波,非线性滤波,Huber,M估计,鲁棒性

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Abstract:

Cubature卡尔曼滤波器(CKF)在非高斯噪声或统计特性未知时滤波精度将会下降甚至发散,为此提出了统计回归估计的鲁棒CKF算法.推导出线性化近似回归和直接非线性回归的鲁棒CKF算法,直接非线性回归克服了观测方程线性化近似带来的不足.具有混合高斯噪声的仿真实例比较了3种Cubature卡尔曼滤波器的滤波性能,结果表明这两种鲁棒CKF滤波精度及估计一致性明显优于CKF,直接非线性回归的CKF的鲁棒性更强,滤波性能更好.

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