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组合导航中软故障难以检测,致使卡尔曼滤波精度降低甚至发散.为提高滤波的容错性,提出了一种基于遗传模糊控制的智能自适应滤波算法.首先针对软故障提出一种模糊自适应滤波算法,算法中通过监测观测量新息及其变化率,应用模糊控制系统计算观测质量因子,并对滤波器量测噪声阵进行在线自适应调整,从而抑制软故障对滤波的影响,保证滤波的精度,提升容错性能.然后,利用自适应遗传算法对隶属度函数的参数进行优化,从而进一步提高算法的整体精度.利用本文提出的算法在SINS/CNS/GPS导航平台上进行了定位实验,结果显示该算法有效,在软故障存在时,定位精度小于2 m,测速精度小于0.1 m/s.
The soft fault in integrated navigation is hard to detect, resulting in the decrease or even the divergence of Kalman filter’s accuracy.In order to improve the fault tolerance of the filter, an intelligent adaptive filtering algorithm based on genetic fuzzy control is proposed.First, a fuzzy adaptive filtering algorithm In the algorithm, by observing the observed information and its rate of change, the fuzzy control system is used to calculate the observed quality factor, and the filter measurement noise matrix can be adjusted online adaptively so as to suppress the influence of soft faults on the filtering and ensure the filtering accuracy , And improve the performance of fault tolerance.Secondly, the parameters of membership function are optimized by using adaptive genetic algorithm to further improve the overall accuracy of the algorithm.According to the algorithm proposed in this paper, positioning experiments are carried out on SINS / CNS / GPS navigation platform, the results show The algorithm is effective. In the presence of soft faults, the positioning accuracy is less than 2 m, and the speed accuracy is less than 0.1 m / s.