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针对弹道导弹飞行中GNSS/SINS深组合导航系统呈现的强机动、非线性特性,引入了基于三阶球面-径向准则的容积卡尔曼(CKF)非线性滤波方法。同时,提出了一种自适应抗差容积卡尔曼滤波(ARCKF)算法,该算法运用抗差M思想,调节量测噪声阵,以抵御系统观测异常扰动,采用自适应因子对协方差阵进行调节,进一步处理动态扰动引入的误差。实验结果表明,该滤波算法有效提高了组合导航的动态性能,在加速度达到60g的强机动仿真环境中,仍能保持较高的导航精度和跟踪性能。
In view of the strong maneuvering and nonlinear characteristics of GNSS / SINS deep integrated navigation system during the ballistic missile flight, a volumetric Kalman nonlinear filtering method based on the third-order spherical-radial criterion is introduced. At the same time, an adaptive robust Kalman filter (ARCKF) algorithm is proposed. This algorithm applies the idea of resistance difference M to adjust the measurement noise matrix to prevent the system from observing the abnormal disturbance. The adaptive factor is used to adjust the covariance matrix , To further deal with the error introduced by dynamic disturbance. The experimental results show that the proposed filtering algorithm can effectively improve the dynamic performance of integrated navigation, and still maintain high navigation accuracy and tracking performance under strong maneuver simulation environment with acceleration of 60g.