中国空间科学技术

中国空间科学技术 ›› 2023, Vol. 43 ›› Issue (5): 65-70.doi: 10.16708/j.cnki.1000-758X.2023.0069

• 巨型星座/低轨大规模星座专栏 • 上一篇    下一篇

基于DRL的巨型星座星地测控链路规划算法

席超1，杨博1，王记荣1，李公2，朱睿杰2，杨肖1   

  1. 1 航天恒星科技有限公司，西安710000
    2 郑州大学，郑州450001

  • 出版日期:2023-10-25 发布日期:2023-09-12

DRL-based link planning algorithm for mega constellation satellite and TT&C

XI Chao1，YANG Bo1，WANG Jirong1，LI Gong2，ZHU Ruijie2，YANG Xiao1   

  1. 1 Satellite Communications Business Division,Space Star Technology Co.，Ltd.，Xi′an 710000，China
    2 Zhengzhou University，Zhengzhou 450001，China
  • Published:2023-10-25 Online:2023-09-12

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摘要： 针对巨型星座的星地测控链路规划问题，提出了一种基于深度强化学习的智能规划调度算法。该方法考虑了卫星对于测控站的资源竞争关系和连接关系，设计了环境状态，决策智能体通过感知卫星状态，结合动作选择策略，生成卫星对于测控站的分配方案，并根据反馈的奖励值进行策略的迭代优化。将本算法应用于巨型星座系统的星地测控链路规划任务，仿真结果表明所提出的智能算法可以将测控站天线利用率提升到98%以上，同时有效地降低了天线的切换次数。另外，训练好的模型可以根据未来时刻的星地可视窗口，在30s内快速生成星地测控链路规划方案。

关键词: 巨型星座, 星地测控链路规划, 深度强化学习, 天线利用率, 切换次数

Abstract: Aiming at the planning of satellite and TT&C links in mega constellations，an intelligent planning and scheduling algorithm based on deep reinforcement learning was proposed.The resource competition and connection relationship between satellite and TT&C station were considered，the environment state was designed，and the allocation scheme of satellite to TT&C station was generated by sensing the satellite state and combining the action selection strategy.Iterative optimization of the strategy was performed according to the feedback reward value.The proposed algorithm was applied to the satellite and TT&C link planning task of the mega constellation system.The simulation results show that the proposed intelligent algorithm can improve the antenna utilization rate of TT&C station to more than 98%，and can effectively reduce the frequency of antenna switching.The trained model can quickly generate the satellite and TT&C link planning scheme within 30s according to the satellitebased visual window at the future time.

Key words:  , mega constellations, satellite and TT&, C links, deep reinforcement learning, antenna utilization, switching times