H ∞ 模糊自适应容积卡尔曼滤波

H_∞ fuzzy adaptive cubature Kalman filter

针对滤波过程中噪声统计特性不准确及非零均值噪声统计特性的情况,本文依据H∞卡尔曼滤波和容积卡尔曼滤波理论,设计了一种H∞模糊自适应容积卡尔曼滤波方法,有效地提高滤波的精度以及对系统未建模动态的鲁棒性。考虑到容积卡尔曼滤波过程中需要已知噪声的先验统计特性的情况,提出了一种模糊自适应方法对系统噪声和测量噪声进行估计,从而提高滤波的稳定性和收敛的快速性。通过仿真实验表明:本文提出的H∞自适应容积卡尔曼滤波能够对噪声特性进行有效的估计,在系统存在参数摄动的情况下具有更高的鲁棒性。

Considering the inaccurate characteristics of noise statistics and the characteristics of non-zero mean noise statistics in the filtering process,in this paper,the H∞fuzzy adaptive cubature Kalman filtering is designed based on the cubature Kalman filtering and H∞filtering theory.Thus,the filter accuracy and robustness of the system unmodeled dynamics are improved effectively.Considering that a priori statistics characteristics of the noise that has been known are necessary during the cubature Kalman filtering process,a fuzzy adaptive method is proposed for estimation of the system noise and measurement noise,so as to improve stability of the filtering and the rapidity of convergence.The simulation results demonstrate that the H∞fuzzy adaptive cubature Kalman filtering is able to effectively estimate the noise characteristics and is more robust under the system perturbations.