模糊自适应Kalman滤波算法在SINS/DR组合导航的应用

Application of Fuzzy Adaptive Kalman Filtering Algorithm in SINS/DR Integrated Navigation

针对里程仪测量误差导致组合导航精度降低的问题,提出基于系统工作状态和滤波器新息状态相结合的模糊自适应算法。根据新息的变化确定模糊规则,修正里程仪输出增益,使新息始终保持在零均值附近,利用修正后的新息修正观测噪声方差,降低导航定位的偏差。仿真实验结果证明,该算法能够很好地提高组合导航定位的精度。

Aiming at the problem that odometer measurement error leads to the reduction of integrated navigation accuracy,a fuzzy adaptive algorithm based on the combination of system working state and filter innovation state is proposed.According to the change of the innovation,the fuzzy rules are determined,and the output gain of the odometer is corrected,so that the innovation is always kept near the zero mean value,and the observation noise variance is corrected by using the corrected innovation,so that the deviation of the navigation positioning is reduced.The simulation results show that this algorithm can improve the accuracy of integrated navigation and positioning.