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提出了一种模糊基函数网络(FBFN)辅助扩展卡尔曼滤波(EKF)的PL(伪卫星)/INS(惯性导航)紧组合导航系统多故障诊断及识别方法.分析了PL/INS紧组合导航系统观测方程的线性化误差,在此基础上利用FBFN对观测方程泰勒展开式Hessian矩阵进行学习,实际应用中,将FBEN的输出作为EKF观测方程的输入项进行滤波。最后,利用大数定律对滤波残差进行平稳性检验,实现了故障诊断以及故障参数识别。仿真结果表明,针对导航系统中多个PL信号同时发生故障的情况,此方法能有效检测故障,并能准确识别出故障参数。
A multi-fault diagnosis and identification method for PL (Pseudolite) / INS (tight navigation) tight integrated navigation system based on fuzzy basis function network (FBFN) and auxiliary extended Kalman filter (EKF) Based on this, we use the FBFN to study the Taylor expansion Hessian matrix of the observation equation. In practice, the FBEN output is filtered as the input term of the EKF observation equation. Finally, using the Law of Large Numbers to test the smoothness of the filtered residuals, fault diagnosis and fault parameter identification are realized. The simulation results show that this method can effectively detect the fault and identify the fault parameters accurately when multiple PL signals in the navigation system simultaneously fail.