宇航学报 ›› 2021, Vol. 42 ›› Issue (11): 1427-1438.doi: 10.3873/j.issn.1000-1328.2021.11.009

• 制导、导航、控制与电子 • 上一篇    下一篇

基于相对成像时刻编码遗传算法的敏捷成像卫星任务规划

韩鹏,郭延宁,李传江,李文博,马广富   

  1. 1. 哈尔滨工业大学控制科学与工程系,哈尔滨 150001;
    2.北京控制工程研究所,北京 100190;
    3.空间智能控制技术重点实验室,北京 100190
  • 收稿日期:2021-02-13 修回日期:2021-03-19 出版日期:2021-11-15 发布日期:2021-11-15
  • 基金资助:
    国家自然科学基金(61973100,61876050);国家优秀青年科学基金(62022013)

A Relative Imaging Time Coding based Genetic Algorithm for Agile Imaging Satellite Task Planning

HAN Peng, GUO Yan ning, LI Chuan jiang, LI Wen bo, MA Guang fu   

  1. 1. Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, China;2. Beijing Institute of Control Engineering, Beijing 100190, China;3. Science and Technology on Space Intelligent Control Laboratory, Beijing 100190, China      
  • Received:2021-02-13 Revised:2021-03-19 Online:2021-11-15 Published:2021-11-15

摘要: 基于相对成像时刻编码方式,提出一种适用于敏捷成像卫星任务规划的自适应遗传算法(RITC AGA)。首先,综合考虑对地凝视成像点目标观测收益与卫星姿态转移期间能耗,构建了卫星任务规划指标函数;其次,基于线性化的姿态动力学模型求解了单次目标间能量最优姿态机动;再次,为确保遗传算法对决策变量有完整的搜索空间并提升迭代效率,设计了一种相对成像时刻编码与解码规则,可适用于规划周期长、卫星对目标有多个时间窗口的情况。最后,通过典型任务规划算例下的对比仿真实验验证了本文所设计方法的有效性与优越性。


关键词: 敏捷成像卫星, 任务规划;最优控制;相对成像时刻编码;遗传算法

Abstract: Based on the relative imaging time coding method, a novel adaptive genetic algorithm (RITC AGA) for imaging satellite task planning is proposed in this paper. Firstly, the objective function of satellite task planning is constructed by considering the observation profit of imaging point targets and the energy consumption during satellite attitude maneuver. Secondly, the optimal attitude transfer model between different targets is developed based on the linearized attitude dynamics model. Then, in order to ensure that the genetic algorithm has a complete search space for decision variables and improve the iteration efficiency, a relative imaging time encode and decode strategy is designed,which can be used in the situation of long term operation and multiple observable time window. Finally, the effectiveness and superiority of the proposed method are verified by the comparative simulation experiments under typical task planning examples.


Key words: Agile imaging satellite, Task planning, Optimal control, Relative imaging time coding, Genetic algorithm

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