AI 中文总结
针对含不确定性的卫星星座重构问题，提出多级星座重构问题的随机变体，采用随机对偶动态整数规划求解，实验验证其性能优于其他随机求解方法。
AI 中文摘要
观测任务规划对卫星运行至关重要，可实现行星现象观测、轨道碎片监测和空间态势感知。为提升卫星运行效能，轨道机动性作为星座可重构性中的前沿作战概念被引入，以应对动态事件。现有星座重构研究均基于确定性任务环境，其模型假设环境为完全先验已知，但观测目标在任意时刻本质上存在不确定性。因此，卫星运行调度必须考虑不确定性以确保观测任务规划充足。针对该问题，本文提出多级星座重构问题（MCRP）的随机变体，采用随机对偶动态整数规划（SDDiP）求解，同时探索其他随机问题求解技术以进行解质量对比。为验证各求解方法，开展两项含随机目标属性的计算实验：第一项针对随机轨道目标，第二项针对模拟飓风。实验结果表明，SDDiP求解方法相比其他随机问题求解方法更具有效性。总体而言，随机MCRP在满足可见时间窗口和机动可行性的同时，可考虑目标随机性。
英文摘要
Observation tasking is critical to satellite operations, enabling observation of planetary phenomena, orbital debris monitoring, and space domain awareness. To improve the effectiveness of satellite operations, orbital maneuverability is introduced as a leading-edge concept of operations within constellation reconfigurability for response to dynamic events. Previous investigations regarding constellation reconfigurability consist of deterministic mission environments, in which the formulations consider a priori knowledge of the environment; however, observation objectives inherently involve uncertainty at any given time. As such, scheduling satellite operations must account for uncertainties to ensure adequate observation tasking. In response, we present a stochastic variant of the Multistage Constellation Reconfiguration Problem (MCRP) which is solved using Stochastic Dual Dynamic Integer Programming (SDDiP). We additionally explore other stochastic problem-solving techniques for solution quality comparison. To demonstrate each solution method, two computational experiments with stochastic target properties are conducted. The first concerns random orbital targets, and the second concerns simulated hurricanes. The results of the experiments demonstrate the effectiveness of the SDDiP solution approach over other stochastic problem-solving methods. Overall, the stochastic MCRP accounts for target stochasticity while obeying visible time windows and maneuver feasibility.
Comments34 pages
