SINS/GNSS/CNS组合导航自适应容错联邦滤波方法

针对子系统发生缓变故障会影响联邦滤波器精度的问题,分析了信息分配因子对子滤波器精度和鲁棒性、全局估计精度以及故障检测效率的影响.在此基础上,研究了一种自适应容错联邦滤波方案.通过对量测噪声阵进行自适应调节来降低未检测出来的故障信息对故障子滤波器和全局估计精度的影响,进而提升无故障子滤波器的精度和系统重构能力;根据子滤波器故障检测函数值来动态调节信息分配因子,可进一步提升故障检测效率.仿真结果表明,相比于传统的容错联邦滤波,该方法能有效降低故障信息对滤波精度的影响,具有较高的全局估计精度.

Adaptive fault tolerance federated filter method for SINS/GNSS/CNS integrated navigation

The accuracy of federated filter will reduce as a result of the gradual fault that occurs on the subsystem. To solve this problem, the influences of information sharing factor on the robustness and accuracy of local filters, the accuracy of global estimation, and the fault detection rate are investigated. On this basis, an adaptive fault tolerance federated filter scheme is presented. The measurement noise covariance matrix is adjusted adaptively to reduce the influence of missed detection fault on the sub-filter and global estimation, which can improve the precision of normal sub-filter and the reconstruction ability of system in return. Besides, the information sharing factor is adjusted dynamically based on the fault detection function to improve the fault detection performance. The simulation results show that compared with the traditional fault tolerance federated filter, this method can reduce the influence of fault on filter accuracy effectively, and has better global accuracy.