In real applications, non-Gaussian distributions are frequently caused by outliers and impulsive disturbances, and these will impair the performance of the classical cubature Kalman filter (CKF) algorithm. In this letter, a modified generalized minimum error entropy criterion with fiducial point (GMEEFP) is studied to ensure that the error comes together to around zero, and a new CKF algorithm based on the GMEEFP criterion, called GMEEFP-CKF algorithm, is developed. To demonstrate the practicality of the GMEEFP-CKF algorithm, several simulations are performed, and it is demonstrated that the proposed GMEEFP-CKF algorithm outperforms the existing CKF algorithms with impulse noise.

翻译：在实际应用中，非高斯分布常由异常值和脉冲干扰引起，这会降低经典容积卡尔曼滤波（CKF）算法的性能。本文研究了一种带基准点的改进广义最小误差熵准则（GMEEFP），以确保误差收敛至零附近，并基于该准则提出了一种新的CKF算法——GMEEFP-CKF算法。为验证GMEEFP-CKF算法的实用性，进行了多项仿真实验，结果表明，所提出的GMEEFP-CKF算法在处理脉冲噪声时优于现有的CKF算法。