一种空间目标轨道状态动态推理方法

Dynamic inference method for the orbit status of space objects

针对非合作空间目标轨道状态的不确定性,提出一种基于动态贝叶斯网络的空间目标轨道状态动态推理方法。首先建立了空间目标轨道状态语义模型,明确了轨道状态与轨道类型、轨道变化间的语义关系;其次,分析了轨道状态的特性,构建了轨道变化中共面变轨和异面变轨的等级划分方法;然后,基于动态贝叶斯网络建立空间目标轨道状态推理模型,利用空间目标轨道类型、轨道变化和轨道状态之间的关系,推理轨道状态的动态变化过程;最后,以不同轨道类型的空间目标为案例对提出的方法进行验证,并与实际情况进行对比。实验结果表明,这种空间目标轨道状态动态推理方法能够对具有不确定性的轨道状态进行推理,获取轨道状态的变化过程。构建的空间目标轨道状态动态推理方法能够为进一步的决策提供支持和辅助。

Aiming at the uncertainty of the orbit status of non-cooperative space objects,a dynamic inference method for the orbit status of space objects based on dynamic Bayesian networks is proposed.First,the semantic model for the orbit status of space objects is established,and the semantic relationships such as the orbit status,orbit class and orbit change are explained.Second,the orbit status characteristics are analyzed,and the hierarchical division method for coplanar and noncoplanar orbit change is constructed.Then,based on the dynamic Bayesian network,an inference method for the orbit status of space objects is established,and the relationships between orbit status,orbit class,and orbit change are used to obtain the dynamic change process of the orbit status.Finally,the proposed method is validated by comparing with actual situations of space objects of different orbital classes.Experimental results demonstrate that the proposed dynamic inference method for the orbit status of space objects can inference the orbit status with uncertainty and obtain the change process,which provides support and assistance for further decision-making.