HXMT卫星长期任务规划算法

黄跃; 屈进禄; 贾淑梅; 马想; 宋黎明; 陈黎; 张文昭

doi:10.11728/cjss2017.06.766

HXMT卫星长期任务规划算法

doi: 10.11728/cjss2017.06.766

1. 中国科学院高能物理研究所粒子天体物理重点实验室北京 100049;
2. 北京师范大学天文学系北京 100875

基金项目:

国家自然科学基金项目（11403026）和中国科学院空间科学战略性先导科技专项项目（XDA04010300）共同资助

详细信息

作者简介:
黄跃,huangyue@ihep.ac.cn

中图分类号: P171.3
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出版历程
- 收稿日期: 2016-12-06
- 修回日期: 2017-07-02
- 刊出日期: 2017-11-15

Long-term Planning Algorithm for the HXMT Mission

1. Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049;
2. Department of Astronomy, Beijing Normal University, Beijing 100875

摘要

摘要: 硬X射线调制望远镜（HXMT）卫星是中国首颗空间X射线天文卫星.为充分利用卫星资源，使科学产出最大化，需要进行长期任务规划.长期任务规划是一个复杂的多目标优化问题.通过分析HXMT观测特点和约束条件，建立了HXMT长期任务规划问题模型，并采用贪婪算法加遗传算法对模型进行求解.实例分析结果表明该方法能够有效解决HXMT长期任务规划问题.
- 硬X射线调制望远镜 /
- 长期任务规划 /
- 贪婪算法 /
- 遗传算法
Abstract: Hard X-ray Modulation Telescope (HXMT) satellite is China's first space X-ray astronomy satellite. The planning and scheduling of HXMT observations is a complex multi-objective optimization problem, and the optimization object is to maximize simultaneously the scientific return and the observation efficiency. By analyzing the characteristics of HXMT observations and all the important factors in the efficient scheduling of a celestial source, such as celestial constraints and the additional scientific constraints, the HXMT long-term planning model is established. The greedy algorithm and genetic algorithm are combined to solve the model. Simulation results show that the approach is effective in solving the HXMT long-term planning problem, based on the analysis of the first year observations of Suzaku Mission.
- HXMT /
- Long-term planning /
- Greedy algorithm /
- Genetic algorithm

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参考文献(15)

[1]	LI Tipei, WU Mei. The hard X-ray modulation telescope mission[J]. Physics, 2008, 37(9):648-651(李惕碚, 吴枚. 空间硬X射线调制望远镜[J]. 物理, 2008, 37(9):648-651)
[2]	LU Yu, ZHANG Wenzhao, QU Jinlu, et al. Observation constraints of the hard X-ray modulation telescope HXMT[J]. Sci. China Phys. Mech. Astron., 2010, 53(S1):31-35
[3]	JOHNSTON M D, MILLER G E. SPIKE:intelli-gent scheduling of Hubble space telescope observa-tions[C]//Intelligent Scheduling. San Francisco:Morgan-Kau-fmann, 1994:391-422
[4]	PRALET C, VERFAILLIE G. AIMS:a tool for long-term planning of the ESA INTEGRAL mission[C]//The 6th International Workshop on Planning and Scheduling for Space (IWPSS-09). Pasadena, USA:IWPSS, 2009
[5]	LAVAGNA M, CASTELLINI F. Advanced Planning and Scheduling Initiative's XMAS tool:AI for automatic scheduling of XMM-Newton long term plan[C]//The 6th International Workshop on Planning and Scheduling for Space (IWPSS-09). Pasadena, USA:IWPSS, 2009
[6]	WU Haiyan, MENG Xin, ZHANG Yuzhu, et al. Research on the planning method for astronomy observation mission[J]. Chin. J. Space Sci., 2013, 33(5):561-568(吴海燕, 孟新, 张玉珠, 等. 面向天文观测的空间科学卫星任务规划方法研究[J]. 空间科学学报, 2013, 33(5):561-568)
[7]	LIU Wen, LI Ligang. Mission planning of space astronomical satellite based on improved genetic algorithm[J]. Comput. Simul., 2014, 31(12):54-58(刘雯, 李立钢. 基于改进遗传算法的天文卫星任务规划研究[J]. 计算机仿真, 2014, 31(12):54-58)
[8]	LIU Wei. Intelligent Controlling Model of HXMT Astronomy Satellite Using MOGA for Scanning the Celestial Sphere[D]. Beijing:Graduate University of Chinese Academy of Sciences, 2006(刘薇. 基于MOGA的HXMT天文卫星巡天扫描智能规划模型[D]. 北京:中国科学院研究生院, 2006)
[9]	CORMEN T T, LEISERSON C E, RIVEST R L. Introduction to algorithms[M]. McGraw-Hill, 2001
[10]	XUAN Guangnan, CHENG Runwei. Genetic Algorithms and Engineering Design[M]. Beijing:Science Press, 2000(玄光男, 程润伟. 遗传算法与工程设计[M]. 北京:科学出版社, 2000)
[11]	WU Hao, LI Ziyang, HU Jian, et al. Formulation of the satellite observation scheme of an area based on greedy algorithm[J]. Remote Sens. Inf., 2010(1):3-6, 31(吴昊, 李子扬, 胡坚, 等. 基于贪婪算法的卫星区域观测方案制定[J]. 遥感信息, 2010(1):3-6, 31)
[12]	LU Pan, XU Peide. Scheduling of imaging reconnaissance satellites (IRS) based on greedy algorithm[J]. Comput. Simul., 2008, 25(2):37-40(卢盼, 徐培德. 基于贪婪算法成像侦察卫星调度方法研究[J]. 计算机仿真, 2008, 25(2):37-40)
[13]	XU Lei. The research and application of multi-objective optimization problem based on the genetic algorithm[D]. Changsha:Central South University, 2007(徐磊. 基于遗传算法的多目标优化问题的研究与应用[D]. 长沙:中南大学, 2007)
[14]	YAMAOKA K. The suzaku mission[C]//Science with the New Generation of High Energy Gamma-Ray Experiments. Science with the New Generation of High Energy Gamma-Ray Experiments, 2007
[15]	Suzaku AO-1 target list[EB/OL]. 2006. http://www.a-stro.isas.jaxa.jp/suzaku/accept/ao1/