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.
@article{arxiv.2307.01438,
title = {Cubature Kalman filter Based on generalized minimum error entropy with fiducial point},
author = {Jiacheng He and Gang Wang and Zhenyu Feng and Shan Zhong and Bei Peng},
journal= {arXiv preprint arXiv:2307.01438},
year = {2023}
}