航空学报 > 2018, Vol. 39 Issue (10): 322066-322066   doi: 10.7527/S1000-6893.2018.22066

基于地面任务-空间姿态映射的敏捷卫星任务规划

赵琳, 王硕, 郝勇, 刘源, 柴毅   

  1. 哈尔滨工程大学 自动化学院, 哈尔滨 150001
  • 收稿日期:2018-01-31 修回日期:2018-07-02 出版日期:2018-10-15 发布日期:2018-07-20
  • 通讯作者: 郝勇 E-mail:haoyong@hrbeu.edu.cn
  • 基金资助:
    国家自然科学基金(61633008);黑龙江省博士后科研启动金(LBH-Q14054)

Mission planning for agile satellite based on the mapping relationship between ground missions and spatial attitudes

ZHAO Lin, WANG Shuo, HAO Yong, LIU Yuan, CHAI Yi   

  1. College of Automation, Harbin Engineering University, Harbin 150001, China
  • Received:2018-01-31 Revised:2018-07-02 Online:2018-10-15 Published:2018-07-20
  • Supported by:
    National Natural Science Foundation of China (61633008); Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province of China (LBH-Q14054)

摘要: 面向观测时间窗口相互重叠的多点目标观测任务需求,对敏捷卫星单星单轨任务规划问题进行研究。针对传统方法在卫星机动能力受限和成像任务冗余两种情况下求解效率低的缺陷,引入任务-姿态协同规划思想。首先,建立地面任务和空间姿态映射关系,并考虑相邻任务间姿态机动时间的最优性使得卫星在观测相邻任务时无多余等待时间,以此来设计任务-姿态协同规划数学模型。其次,根据任务-姿态协同规划数学模型,设计自适应伪谱遗传算法(APGA),用以求解满足调整时间最优性的敏捷卫星任务规划问题。最后,通过仿真实验,验证了模型和算法能够有效地解决传统算法求解敏捷卫星任务规划问题时存在的求解效率低的缺陷。

关键词: 敏捷卫星, 任务规划, 地面任务, 空间姿态, 自适应伪谱遗传算法

Abstract: To address the requirement for multi-target observation in an overlapping time window, the task scheduling of a single agile satellite with a single orbit is studied. The traditional algorithm lacks effectiveness due to the limitation of maneuvering capability and the redundancy of imaging mission. To improve the effectiveness, the collaborative planning of mission and attitude is proposed in this paper. First, the collaborative planning model of the mission and attitude is designed by establishing a mapping relationship between ground missions and spatial attitudes and by examining the optimality of attitude adjustment time between adjacent missions, which ensures that the satellite has no extra waiting time when observing adjacent missions. Then, based on the characteristics of the model, an Adaptive Pseudo-spectral Genetic Algorithm (APGA) is proposed to obtain the optimal adjustment time in mission planning of the agile satellite. Finally, simulation experiments are used to verify the enhanced effectiveness of the model and the algorithm proposed.

Key words: agile satellite, mission planning, ground missions, spatial attitudes, adaptive pseudo-spectral genetic algorithm

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