To degrade the adverse effects of biases in the direct inertial navigation system/global navigation satellite system integration, a novel robust partly strong tracking consider state-dependent Riccati equation filter (PSTCSDREF) algorithm is proposed. A nonlinear "consider" approach is utilized to incorporate statistics of biases into state estimation error covariance of the state-dependent Riccati equation filter (SDREF), and a new consider SDREF(CSDREF) is proposed. Then, the prediction covariance of the state is partly multiplied by a strong tracking factor, which does not include the bias covariance, to mitigate the adverse effects navigation performance of model uncertainties. Numerical simulation demonstrates that the proposed PSTCSDREF has a better navigation accuracy comparing with extended Kalman filter, SDREF, and CSDREF.

中文翻译：

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稳健的部分强跟踪考虑 SDRE 过滤器，用于直接 INS/GNSS 集成与偏差

为了降低直接惯性导航系统/全球导航卫星系统集成中偏差的不利影响，提出了一种新颖的鲁棒部分强跟踪考虑状态相关的Riccati方程滤波器（PSTCSDREF）算法。利用非线性“考虑”方法将偏差统计纳入状态相关Riccati方程滤波器(SDREF)的状态估计误差协方差，并提出了一种新的考虑SDREF(CSDREF)。然后，将状态的预测协方差部分乘以不包括偏差协方差的强跟踪因子，以减轻模型不确定性对导航性能的不利影响。数值模拟表明，与扩展卡尔曼滤波器、SDREF 和 CSDREF 相比，所提出的 PSTCSDREF 具有更好的导航精度。