基于自适应SRCKF的空间非合作目标实时轨道确定

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.

An Improved Adaptive SRCKF Algorithm for Non-Cooperative Target Orbit Determination

A novel filtering algorithm for orbit determination of non-cooperative target is proposed to cope with the simplified dynamic model error problem. The algorithm is based on Nonlinear Predictive Filter(NPF) and Square Root Cubature Kalman Filter(SRCKF) and is called Adaptive Square Root Cubature Kalman Filter(ASRCKF).In the filtering process, NPF is used to modify the orbit dynamic model which takes into account J2 perturbation and SRCKF takes the revised model for state estimation.Simulation results of the application to Geostationary Earth Orbit(GEO) spacecraft orbit determination of non-cooperative Low Earth Orbit(LEO) targets show that the proposed algorithm has higher tracking precision, stronger robustness and stability than traditional filter