标题： 基于混合整数线性规划的卫星星座配置最优设计 显示英文标题

标题： Optimal Design of Satellite Constellation Configurations with Mixed Integer Linear Programming

摘要： 设计卫星星座系统涉及复杂的多学科优化，其中覆盖范围是影响整体系统成本和性能的主要因素。 在各种设计考虑中，星座配置——即卫星相对于彼此的放置和分布方式——主要决定了最终的覆盖范围。 在星座配置设计中，覆盖范围可以被视为目标或约束，这取决于任务目标。 现有文献针对每种情况分别处理，应用一组独特的假设、建模和求解方法。 尽管这种基于问题的方法是有价值的，但用户在跨不同任务场景进行权衡研究时常常面临实现上的挑战，因为每个场景都必须单独处理。 为此，我们提出了一种统一的框架，该框架包含五个混合整数线性规划公式，具有实际意义，可以通过添加额外约束扩展到更复杂的任务叙述，并能够获得可证明最优的星座配置。 它可以处理各种指标和任务场景，例如百分比覆盖范围、平均或最大重访时间、固定数量的卫星、时空变化的覆盖需求，以及地面、空中或空间基的静态或移动目标。 本文介绍了多个附加功能、案例研究和比较分析，以展示所提出的框架的灵活性。 显示英文摘要

摘要： Designing satellite constellation systems involves complex multidisciplinary optimization in which coverage serves as a primary driver of overall system cost and performance. Among the various design considerations, constellation configuration -- how satellites are placed and distributed in space relative to each other -- predominantly determines the resulting coverage. In constellation configuration design, coverage can be considered either as an objective or a constraint, driven by mission objectives. State-of-the-art literature addresses each situation on a case-by-case basis, applying a unique set of assumptions, modeling, and solution methods. Although such a problem-based methodology is valuable, users often face implementation challenges when performing trade-off studies across different mission scenarios, as each scenario must be handled distinctly. In response, we propose a unifying framework consisting of five mixed-integer linear program formulations that are of practical significance, extensible to more complex mission narratives using additional constraints, and capable of obtaining provably optimal constellation configurations. It can handle various metrics and mission scenarios, such as percent coverage, average or maximum revisit times, fixed number of satellites, spatiotemporally varying coverage requirements, and ground-, aerial-, or space-based, static or mobile targets. The paper presents several add-ons, case studies, and comparative analyses to demonstrate the versatility of the proposed framework.