一种基于可观测度分析的SINS/GPS自适应-反馈校正滤波新方法

 针对机载捷联惯导系统(SINS)/全球定位系统（GPS）组合导航系统不完全可观测导致滤波器精度下降甚至发散的问题，提出了一种基于系统状态可观测度分析的自适应反馈校正滤波新方法。该滤波方法改进了系统可观测度的归一化处理方法，将归一化处理后的系统状态可观测度作为反馈因子，对SINS系统进行自适应反馈校正。最后，将该方法应用于机载合成孔径雷达(SAR)运动补偿用SINS/GPS组合导航系统中，飞行试验结果表明该方法在系统不完全可观测的情况下有效地提高了导航精度。

A New Adaptive Feedback Kalman Filter Based on Observability Analysis for SINS/GPS

The feedback Kalman filter is widely used in the data fusion of strapdown inertial navigation system(SINS)/ global position system(GPS) integrated navigation system which is incomplete observable.The accuracy of Kalman filter will degrade so severely that the Kalman filter is likely diverge due to the direct feedback on some system states with lower observability.To solve the problem,a new adaptive feedback Kalman filter based on the observability analysis of system states is presented in this paper.The state estimation is not fed back directly but adaptively fed back through a feedback factor which is the normalized degree of observability of the state.And the normalization method of observable degree is modified in this paper.The new method is applied to the SINS/GPS for airborne synthetic apertute radar(SAR) motion compensation,and the flight test results indicate that this new filter can improve the accuracy of the SINS/GPS integrated navigation system in the incomplete observable condition.