基于Masreliez-Martin的鲁棒分数阶容积卡尔曼滤波算法及应用

doi:10.12305/j.issn.1001-506X.2023.01.27

Abstract

Abstract:

Aiming at the state estimation problem of discrete fractional-order nonlinear system with non-Gaussian measurement noise, a robust fractional-order cubature Kalman filter based on the Masreliez-Martin (M-M) method is proposed. Using the third-order cubature rule to derive the state prediction and refining the measurement update using M-M method, the M-M method based robust fractional cubature Kalman filter for the fractional discrete nonlinear dynamic system is derived. The proposed algorithm is applied to state estimation of the re-entry ballistic target. The simulation results show that the M-M method based robust fractional cubature Kalman filter is better than the fractional unscented filter and fractional cubature Kalman filter. Finally, the influence of contaminated measurement noise on the estimation performance of the M-M based robust fractional cubature Kalman filter algorithm is analyzed, and the results show that the proposed algorithm has good effectiveness and robustness.

Key words: fractional calculus, cubature Kalman filter (CKF), state estimation, Masreliez-Martin (M-M) method

CLC Number:

TP273

Jing MU, Dongsheng YAN, Yuanli CAI, Changyuan WANG. Masreliez-Martin method based robust fractional cubature Kalman filtering algorithm and its applications[J]. Systems Engineering and Electronics, 2023, 45(1): 234-240.

Figures/Tables 8

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References 32

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Masreliez-Martin method based robust fractional cubature Kalman filtering algorithm and its applications

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