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首页> 外文期刊>Journal of signal processing systems for signal, image, and video technology >A Feature Selection Model to Filter Periodic Variable Stars with Data-sensitive Light-variable Characteristics
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A Feature Selection Model to Filter Periodic Variable Stars with Data-sensitive Light-variable Characteristics

机译：具有数据敏感光变量特性的过滤周期变量星的功能选择模型

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摘要

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.
机译：目前，航天器的自主管理和运营是太空技术发展的主要方向和目的，以减轻地面测量和控制的负担，降低运营成本和管理，扩大航天器的应用范围。为了在宇宙飞船的给定条件下选择具有一定数量的合适的周期性变量恒星，我们研究了光学变量航天器的自主导航方法，提出了一种特征选择模型，以过滤具有光变量特性的周期性变量恒星。它主要专注于脉动光学变频星时钟模型的学习过程，具有测量方法的高精度脉动光学可变自主导航算法和光学可变光变化特性机制。从实验中，选择周期性变量星的样品，形成132个初始候选样品和16个导航样本星的数据库。因此，可以进行时间测量以利用周期性变量恒星的性质，即其周期，基于地基观察和基于地面的应用，可以通过宽的周期性可变星形观察来进行。它可以满足航天器的要求。

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