摘要
为解决具有多次轨道机动能力、多探测目标、多探测器协同的对地观测任务的星下点轨迹规划优化问题,提出一种基于特征参数拟合的星下点轨迹快速计算方法,并采用基于数据库的星下点轨迹拼接方法建立优化模型。首先,对描述星下点轨迹的特征参数进行分析和提炼,采用多项式对特征参数进行拟合实现快速计算;然后,根据探测目标建立观测码数据库,再进一步整理成轨迹数据库;最后,建立基于轨迹数据库的优化模型,解决整个星下点轨迹规划问题。对第11届全国空间轨道设计竞赛的固定目标快速全覆盖任务进行仿真,能够在19.19 d内完成该任务,表明所提设计方法和方案,可用于各类近圆轨道的星下点轨迹设计。
In order to solve the problems related to the ground tracks of satellites for Earth observation with multiple orbital maneuvering capabilities,multi-detection targets,and multi-detector coordination,a fast calculation method of the ground tracks of satellites based on characteristic parameter fitting is proposed.An optimization model is established based on the database about the splicing method of the ground tracks of satellites.Firstly,the characteristic parameters describing the ground tracks of satellites are analyzed and refined,and polynomials are used to fit these characteristic parameters to achieve fast calculation.Then,an observation code database is established according to the detection target,and the database is further organized into a trajectory database.Finally,an optimization model based on the trajectory database is established to solve all problems on the ground tracks of satellites.The simulation of a fast full coverage task for a fixed target in CTOC11(the 11th China Trajectory Optimization Competition)was completed within 19.19 days.The results show that the design method and scheme adopted in this paper can be used for the design of ground tracks of satellites in various near-circular orbits.
作者
黄雄威
王蜀泉
张扬
何胜茂
HUANG Xiongwei;WANG Shuquan;ZHANG Yang;HE Shengmao(CAS Key Laboratory of Space Utilization,Technology and Engineering Center for Space Utilization,Chinese Academy of Sciences,Beijing 100094,China;University of Chinese Academy of Sciences,Beijing 100049,China;Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China)
出处
《中国科学院大学学报(中英文)》
CAS
CSCD
北大核心
2024年第5期665-676,共12页
Journal of University of Chinese Academy of Sciences
基金
中国科学院青年创新促进会(2022126)
航天科技集团空间技术研究院CAST基金(2022110033001596)资助。