信息融合算法在空间飞行器自由段跟踪中的应用

Application of Information Fusion Algorithm in Trajectory Tracking of Free Segment Space Vehicle

针对空间飞行器在自由段运动的情况,在自由段创建轨道动力学模型,并讨论多基雷达观测下,基于UKF滤波的集中式融合与分布式融合的相关性能。在集中式融合算法中,运用了基于并行和序贯的滤波方法,在分布式融合方法中,运用了Bar-Shalom-Campo融合以及联邦滤波,并对比了几种滤波算法对在轨道自由段状态估计融合的适用性。仿真结果表明,在自由段目标状态融合中,应优先选用基于UKF滤波的联邦滤波算法。

This paper establishes a dynamics model in the free segment,aiming at the situation of the spacecraft movement in the free segment,and discusses the related performance of centralized fusion and distributed fusion based on UKF filtering under multi-base radar observation.In the centralized fusion algorithm,parallel filtering and sequential filtering algorithms are used,while in the distributed fusion method,simple convex combination fusion,Bar-Shalom-Campo fusion and federated filtering are used,and the applicability of five filtering algorithms to the fusion of state estimation in the free segment of ballistic missile is compared.The simulation results show that the federated filter algorithm based on UKF filtering should be preferred in the free segment target state fusion.