针对合作式航天器实时轨道确定问题,提出一种基于轨道六要素的平方根容积卡尔曼滤波方法(SCKF),该方法采用轨道六要素建模,利用初始方差的物理意义,设置滤波参数,提高算法收敛性和精度,同时,采用改进容积卡尔曼滤波方法——平方根容积卡尔曼滤波方法(SCKF)进行状态估计。仿真算例表明,该方法可有效完成实时轨道确定,且在具有先验信息的情况下估计精度和稳定性比传统方法更好,具有工程应用价值。

In order to solve the problem of real-time orbit determination of cooperative spacecraft, the square root cubature Kalman filter (SCKF) method based on six elements of orbit is proposed. This method establishes a dynamic model for the six elements of the orbit. Considering the physical meaning of the initial variance, this method can set the filter parameters more accurately, thus improving the convergence and accuracy of the algorithm. At the same time, the method uses the improved Cubature Kalman filter method (SCKF) for state estimation. The simulation example shows that the method can effectively complete the real-time orbit determination, and the estimation accuracy and stability are better than the traditional method in the case of a priori information, which has engineering application value.