【摘要】 载体在机动的情况下,系统会产生随机非高斯噪声,这些噪声的统计特性不易准确得到。若在组合导航系统中仅采用常规卡尔曼滤波算法,不能得到系统状态的最优估计值,甚至滤波器还有可能发散。文中设计了一种模糊推理系统,并将其与卡尔曼滤波算法相结合,在线修正系统量测噪声协方差阵。仿真结果表明,该模糊卡尔曼滤波算法能很好地对系统状态进行最优估计,同时能很好适应系统噪声的变化,提高了导航系统的精度。更多还原

【Abstract】 The characteristics of the varied statistic of measurement noise is not obtained easily and accurately under the circumstance that the carrier is maneuvering,and much random non-Gauss noise could be produced in the system.If only the normal Kalman filtering algorithm is applied in the integrated navigation system,it has a disadvantage of not getting the optimum values, especially results in non-convergence values.In this paper,a fuzzy inference system(FIS) combined with the Kalman filtering algorithm is presented.It can efficiently adjust the covariance matrix of system measurement noise online.Simulations show this filtering algorithm can get a better result in system states optimization estimation.Simultaneously it has a superiority of adapting system noise variation and may greatly improve the precision of the navigation system.更多还原