At present, autonomous management and operation of spacecraft are the main direction and objective of the development of space technology to lighten the burden of ground measurement and control, reduce the cost of operation and management, and expand the application scope of spacecraft. To select the suitable periodic variable stars with a certain quantity at the given conditions of spacecraft, we study the autonomous navigation method of optical variable spacecraft and propose a feature selection model to filter periodic variable stars with light-variable characteristics. It mainly focuses on the learning processes of the pulsating optical variable light variation star clock model, the high precision pulsating optical variable autonomous navigation algorithm and the optical variable light variation characteristic mechanism with the measurement method. From experiments, the sample of the periodic variable star is selected, forms a database of 132 initial candidate samples and 16 navigation sample stars. So, time measurement can be conducted to take advantage of the nature of periodic variable stars that take days as its cycle, ground-based observation and ground-based application can be conducted with the wide spectrum of periodic variable star observation. It can meet the requirements of spacecraft.

当前，航天器的自主管理和运行是航天技术发展的主要方向和目标，以减轻地面测控的负担，降低运行和管理成本，扩大航天器的应用范围。为了在给定的航天器条件下选择一定数量的合适的周期性变星，我们研究了光学可变航天器的自主导航方法，并提出了一种特征选择模型，对具有光变特征的周期性变星进行滤波。它主要关注脉动光学可变光变星时钟模型的学习过程，高精度脉动光变自主导航算法及光变光变化特征机理的测量方法。从实验中，选择了周期性变星的样本，形成了132个初始候选样本和16个导航样本星的数据库。因此，可以利用以数天为周期的周期性恒星的性质来进行时间测量，可以利用广范围的周期性恒星观测来进行地基观测和地基应用。可以满足航天器的要求。可以利用以数天为周期的周期性恒星的性质来进行时间测量，可以在宽范围的周期性恒星观测中进行地面观测和地面应用。可以满足航天器的要求。可以利用以数天为周期的周期性恒星的性质来进行时间测量，可以在宽范围的周期性恒星观测中进行地面观测和地面应用。可以满足航天器的要求。