基于ATSUKF算法的卫星姿控系统故障估计

Based on the bias-separate principle and the Unscented Kalman Filter (UKF), an Adaptive Two-Stage Unscented Kalman Filter (ATSUKF) is proposed to address the fault estimation of actuators/sensors in the satellite attitude control system. First, the TSUKF is presented. The decoupled state and faults are estimated by applying the bias-separate principle and using the nonlinearity by the UKF when the attitude is maneuvered without linearization of the system model. This avoids lowering the dimension of the matrix during the estimating process. Based on the TSUKF, an adaptive version is proposed. The adaptive matrices are calculated by the residuals in the sliding data window to make the noise covariance matrices change adaptively. With the ATSUKF estimator, the convergence rate is enhanced when the prior knowledge of the noise covariance matrices are inaccurate or the fault changes. Numerical simulations demonstrate the effectiveness of the approach proposed.