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FocusGEO望远镜观测地球同步轨道目标的光度特性分类
引用本文:赵晓芬,郑景辉,毛银盾,于涌,王鲲鹏,温昌礼.FocusGEO望远镜观测地球同步轨道目标的光度特性分类[J].空间科学学报,2022,42(1):136-143.
作者姓名:赵晓芬  郑景辉  毛银盾  于涌  王鲲鹏  温昌礼
作者单位:1.中国科学院上海天文台 上海 200030
基金项目:国家自然科学基金项目资助(11803067);
摘    要:基于FocusGEO望远镜2017年12月至2019年6月的测光观测数据,开展台站上空地球同步轨道(GEO)目标光度曲线的分类研究。通过对GEO卫星光度曲线特征的统计分析,建立了一种全新的GEO卫星分类系统,确定了各类GEO卫星光度曲线的占比,分析了光度特征类别与卫星平台的相关性。本研究将197颗GEO卫星的光度曲线分为六类,其中约90%的卫星可归为三类:典型类、BSS类和Ekspress类。光度特征分类与卫星平台无直接的相关性,但同一类别中平台相同或相近的卫星,具有相似的光度曲线。该分类系统可为位置相近的多个GEO目标的准确识别提供辅助手段,为目标异常监测和物理特性研究提供依据,对空间态势感知具有重要意义。 

关 键 词:GEO目标    光度特征    分类研究    卫星平台
收稿时间:2020-09-28

GEOS Photometric Signature Classifications Based on Observations of FocusGEO Telescopes
ZHAO Xiaofen,ZHENG Jinghui,MAO Yindun,YU Yong,WANG Kunpeng,WEN Changli.GEOS Photometric Signature Classifications Based on Observations of FocusGEO Telescopes[J].Chinese Journal of Space Science,2022,42(1):136-143.
Authors:ZHAO Xiaofen  ZHENG Jinghui  MAO Yindun  YU Yong  WANG Kunpeng  WEN Changli
Institution:1.Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 2000302.University of Chinese Academy of Sciences, Beijing 1000493.Shanghai University, College of Sciences, Shanghai 2004444.Beijing Institute of Tracking and Telecommunication Technology, Beijing 1000945.32035 Troops of PLA, Xi’an 710200
Abstract:Ground-based optical-electrical observation is the main approach to obtain the Geostationary Earth Orbit (GEO) targets’ optical characteristics. Light curve classification was studied based on the photometry observations of FocusGEO telescope at Lijiang Station from December 2017 to June 2019. A new classification system was introduced based on the statistical analysis of GEO satellite light curve features. Moreover, the correlation between light curve classification and satellites’ bus type was analyzed. Results show that photometric signatures of 197 GEO satellites can be classified into six classes and each class can be qualitatively explained by the actual satellite structure. Approximately 90% of these satellites appear to belong to three of six different classes. However, light curve classification has no significant correlation to satellites’ bus types, but for the satellites with the same or similar bus types in each class, the light curves resemble each other. The classification system can aid to identify cluster GEO targets and provide the basis for anomaly detection and physical characteristics research, which is of great significance for space situational awareness. 
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