摘要
暗弱天然卫星与主带小行星相比,具有亮度低、速度变化快的特点.在观测这类天体时,不能简单地延长曝光时间来提高其信噪比.尝试观测多幅短曝光的CCD(chargecoupled device)图像,采用移位堆叠(shift-and-add)方法,希望提高目标成像的信噪比,获得暗弱天然卫星的精确测量结果.使用2018年4月9—12日夜间,中国科学院云南天文台1 m望远镜(1 m望远镜)拍摄的木星5颗暗卫星的229幅CCD图像,实施了移位堆叠试验.为了验证结果的正确性,与相近日期中国科学院云南天文台2.4 m望远镜(2.4 m望远镜)观测的相同木卫图像的测量结果进行了比较和分析.位置归算采用了JPL(Jet Propulsion Laboratory)历表.结果表明,对CCD图像使用移位堆叠方法,通过叠加约10幅曝光时间100 s的图像,1 m望远镜能观测暗至19等星的不规则天然卫星,而且测量的准确度与2.4 m望远镜的测量结果有良好的一致性.
Faint natural satellites have the characteristics of lower brightness and faster movement variation when they are compared with those of Main Belt Asteroids.When observing such satellites,one cannot simply increase the time of exposure to improve their signal-to-noise ratio(SNR).We attempt to obtain multiple short-exposure images and use the shift-and-add method to improve the SNR of target,and then obtain accurate measurement results of faint satellites.The 229 CCD(charge-coupled device)frames of Jupiter’s 5 faint satellites that we obtained by the 1 m telescope at Yunnan Obervatories,Chinese Academy of Sciences(1 m telescope)on April 9—12,2018 are used to carry out the CCD image shift-and-add experiment.And we use the CCD images of the same satellites obtained by the 2.4 m telescope at Yunnan Obervatories,Chinese Academy of Sciences(2.4 m telescope)to verify the correctness of the result.The theoretical positions of the satellites are retrived from the JPL(Jet Propulsion Laboratory)ephemeris.Our results show that using this method,the 1 m telescope of Yunnan Observatories can observe the satellites as faint as about 19 magnitudes,and their accuracies are in good agreement with the corresponding results derived by the 2.4 m telescope.
作者
李灿伟
彭青玉
LI Can-wei;PENG Qing-yu(Department of Computer Science,Jinan University,Guangzhou 510632;Sino-French Joint Laboratory for Astrometry,Dynamics and Space,Jinan University,Guangzhou 510632)
出处
《天文学报》
CSCD
北大核心
2020年第3期91-99,共9页
Acta Astronomica Sinica
基金
国家自然科学基金项目(11873026、 11273014、 11703008)
中国科学院天文联合基金项目(U1431227)资助。
关键词
天体测量学
仪器
望远镜
技术:图像处理
方法:观测
方法:数据分析
astrometry
instrumentation
telescope
techniques:image processing
methods:observational
methods:data analysis