Cubature Kalman filter Based on generalized minimum error entropy with fiducial point

Jiacheng He; Gang Wang; Zhenyu Feng; Shan Zhong; Bei Peng

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arXiv · 2307.01438

Cubature Kalman filter Based on generalized minimum error entropy with fiducial point

Jiacheng He·Gang Wang·Zhenyu Feng·Shan Zhong·Bei Peng

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Abstract

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.

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Jiacheng He, Gang Wang, Zhenyu Feng, Shan Zhong, Bei Peng. 2023-07-04. Cubature Kalman filter Based on generalized minimum error entropy with fiducial point. https://arxiv.org/abs/2307.01438

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