中文摘要：

在INS/GPS组合导航系统的研究中,为了解决非线性滤波算法在系统模型不确定情况下出现的滤波精度低、鲁棒性差的问题,提出了一种将强跟踪滤波算法与容积卡尔曼滤波算法（CKF）相结合的组合导航滤波算法（SMFCKF）。SMCKF算法将强跟踪滤波算法中的多重次优渐消因子引入到CKF算法的状态预测协方差矩阵中,对不同的状态通道进行相应的渐消。通过建立INS/GPS组合导航系统的非线性模型,对改进的滤波算法进行仿真,结果表明改进的滤波算法提高了滤波精度和鲁棒性,滤波效果优于CKF算法,适合应用于INS/GPS组合导航系统中,为飞行器组合导航优化提供了参考。

英文摘要：

In order to solve the poor filtering accuracy and robustness of nonlinear filters when model uncertainty exits, the paper studied the INS/GPS integrated navigation systems, and proposed a SMFCKF algorithm which combines cubature Kalman filter with strong tracking filter. The multiple fading factors of strong tracking filter were added to state forecast covariance matrix of CKF algorithm to fade every status channel. This paper established the nonlinear model of the INS/GPS integrated system, and simulate the improved filter algorithm, simulation results show that the improved filter algorithm improve the filtering accuracy and the robustness, also this filtering algorithm is superior to the CKF filter algorithm and suitable for the INS/GPS integrated navigation system.