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针对天基测角对非合作目标跟踪定轨的动力学模型简化误差问题,提出一种基于非线性预测滤波和SRCKF(Square Root Cubature Kalman Filter,平方根容积Kalman滤波)的自适应滤波方法。采用考虑地球J2摄动影响的轨道动力学模型作为状态方程,在跟踪滤波过程中,用NPF(Nonlinear Predictive Filter,非线性预测滤波)对动力学模型进行实时修正,利用SRCKF对修正后的动力学模型进行状态估计。将该方法应用于高轨航天器对非合作低轨目标的实时测角定轨任务中,进行数字仿真,仿真结果证明,该方法相比传统的滤波方法具有更高的精度、更强的鲁棒性和稳定性。
Aimed at the simplified error of kinetic model of non-cooperative tracking orbit determination by space-based goniometry, an adaptive filtering method based on nonlinear prediction filtering and SRCKF (Square Root Cubature Kalman Filter) is proposed. The orbital dynamics model considering the influence of earth’s J2 perturbation is taken as the equation of state. In the process of tracking and filtering, dynamic model is corrected by NPF (Nonlinear Predictive Filter) in real time. SRCKF is used to modify the corrected kinetics Model for state estimation. The method is applied to the real-time goniometric orbit determination task of the high-orbit spacecraft for the non-cooperative low-rail target, and the numerical simulation is carried out. The simulation results show that this method has higher accuracy and robustness than the traditional filtering method Stick and stability.