容积卡尔曼滤波在空间目标轨道确定中的应用

针对空间监视雷达的近地目标轨道确定问题，提出了基于容积卡尔曼滤波的精密轨道确定方法，与被广泛应用的扩展卡尔曼滤波方法相比，所提方法具有更高的定轨精度. 同时，由于容积卡尔曼滤波在理论上具有严格的数学证明，其在处理空间目标复杂运动问题的过程中具有更好的数值稳定性. 通过引入递推形式的后验克拉美罗界，分析了不同观测模型对定轨性能的影响. 利用仿真数据进一步验证了所提出方法的有效性和分析的正确性.

Cubature Kalman filtering for orbit determination of space targets

For orbit determination of space targets in the low earth orbit, a kind of precise orbit determination method is proposed based on the cubature Kalman filter. Compared with widely used extended Kalman filter, the proposed method provides more accurate state estimation. Moreover, due to the rigorous mathematical proof of the cubature Kalman filter, it achieves good performance on the numerical stability with the complicated motion model during orbit determination. Then, by introducing the sequential posterior Cramér-Rao lower bound, the effect of different radar observation models on the orbit determination performance is analyzed. Finally, using the simulated observation data, the effectiveness of the proposed method and the correctness of the analysis are demonstrated.