一种考虑GPS信号中断的导航滤波算法

针对无人机惯性（INS）/GPS组合导航系统，考虑导航过程中存在的GPS数据中断的问题，设计了一种改进的滤波算法。首先建立了无人机导航运动学模型，再将传统的扩展卡尔曼滤波（EKF）技术和强跟踪滤波结合，利用模糊理论中的隶属度函数设计了一种模糊强跟踪扩展卡尔曼滤波（STEKF）算法。仿真结果表明，所设计的改进算法能够快速适应GPS信号突变，即当GPS信号从故障状态恢复到正常状态时，改进算法相较普通EKF算法能更快速地收敛到稳定状态，重新完成对飞行状态的估计。同时相较普通EKF和强跟踪扩展卡尔曼滤波算法，改进算法具有更高的滤波精度。 

A navigation filtering algorithm considering GPS signal interruption

Aimed at the problem of GPS data interruption in the UAV INS/GPS integrated navigation system, an improved filtering algorithm is designed. Firstly, the kinematics model of UAV navigation is established. Then the traditional extended Kalman filter (EKF) technique and strong tracking filter are combined. A new navigation filtering algorithm is designed by using the membership function in fuzzy theory. The simulation results show that the improved algorithm can quickly adapt to the sudden change of GPS signal. When the GPS signal recovers from the fault state to the normal state, the improved algorithm can converge to the steady state more quickly than the ordinary EKF algorithm, and the flight state is re-completed and estimated. At the same time, compared with the common EKF and strong tracking extended Kalman filter (STEKF) algorithm, the improved algorithm has higher filtering accuracy.