基于模糊理论的抗差Kalman滤波算法

动态导航与定位的质量取决于对动态载体扰动和观测异常扰动的认知和控制质量。在实践中,观测向量及其动态模型信息均可能存在异常,此时若仍利用标准Kalman滤波,则状态滤波解将极不可靠。在标准Kalman滤波原理的基础上,结合模糊控制理论,提出了一种基于模糊理论的抗差Kalman滤波算法。该方法是依据滤波处理后的数据残差,利用模糊理论构造等价权,从而有效控制粗差对导航解的影响,并用算例验证了该方法的可行性和有效性。

Robust Kalman Filtering Algorithm Based on Fuzzy Control

The quality of kinematic navigation and positioning depends on the quality of the kinematic model describing the vehicle movements and the reliability of the observations.The observation vector and the information of its dynamic model may be all abnormal in practice,if still use standard Kalman filtering here,the solution of filtering will be not mighty reliable.According to Kalman filtering,this paper put forward a robust Kalman filtering algorithm based on fuzzy control theory,combining with the fuzzy control theory.The algorithm structured equivalent weight using fuzzy theory based on filtered residual deviation and controled the influence of outlier on navigation results effectively.It was shown,by calculations and analysis,that this way was feasible and effective.