MIMU／GPS组合导航模糊自适应卡尔曼滤波研究

针对组合导航初始对准中存在模型误差时常规卡尔曼滤波容易发散的问题,提出了一种模糊自适应卡尔曼滤波算法。该算法采用模糊控制规则,根据新息的方差和均值变化自适应调整量测噪声权值矩阵。此算法运用于MIMU/GPS组合导航初始对准中,获得了较高的导航精度。仿真结果表明,该算法能够有效防止滤波发散,减少模型误差对滤波结果的影响,提高了滤波精度,实现了参数的在线调整。

On fuzzy adaptive Kalman filtering for MIMU/GPS integrated navigation

Conventional Kalman filtering may get divergent in initial alignment of integrated navigation as model error exists,so we put forward an algorithm of fuzzy adaptive Kalman filtering.According to change of the variance and mean value of new information,fuzzy control rule is used for adjusting the measurement noise weighted-value matrix adaptively.The method can solve divergence problem caused by the insufficient knowledge of the prior filter statistics.The algorithm was applied in initial alignment of MIMU/GPS integrated navigation and greatly improved the navigation accuracy.Simulation result shows that the fuzzy adaptive Kalman filtering can prevent filtering divergence,reduce the influence of model error on filtering result,improve filtering accuracy,and also can implement on-line parameter adjustment.