多变量全局寻优与智能优化在星座组网中的应用

顶层任务规划通常与星座组网紧密结合，小卫星分散灵活的特性尤其适用于星群规模化在轨运行。针对热点区域覆盖和全球覆盖的不同任务需求，提出了对构型多变量进行全局寻优和利用智能优化技术进行星座构型优化的方法，两种优化方法可分别获得小规模星群最优效能与超大型星群的较优效能。优化方法不受轨道类型和任务目标分布的约束，具有良好的鲁棒性。

Application of multi variate global optimization and intelligent optimization in constellation design

Top mission design is usually closely associated with satellite constellation. The decentralized and flexible features of small satellites match the use of large scale constellation in orbit. The application method of multi variate global optimization and intelligent optimization for constellation design was presented with consideration for the different mission requirements of hotspot coverage and global coverage. Therefore, the optimal performance of small constellation and the superior performance of large scale constellation could be obtained. These methods for satellite constellation optimization are not restricted by orbit types and mission target distributions, and show the good performance of robustness.