  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.
