ASTRA：用于动态卫星星座的ADMM加速拓扑重构
ASTRA: ADMM-Accelerated Topology Reconfiguration for Dynamic Satellite Constellations
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中文总结 AI 辅助
ASTRA提出一种基于在线学习和ADMM加速的卫星星座拓扑重构框架，在理论和实验上均优于现有方法，适用于现实低轨网络。
中文摘要 AI 辅助
动态拓扑重构对于大型卫星星座的可靠性和效率至关重要，然而许多现有方法依赖于理想化假设，如星座完全部署或轨道间距均匀。我们提出了基于遗憾感知学习的自适应卫星拓扑（ASTRA），这是一个基于在线学习框架并使其计算上可行的动态卫星拓扑重构的理论基础框架。ASTRA结合了基于ADMM的离线求解器与高效的在线更新（包括在线梯度下降和在线条件梯度），相比通用优化流程，显著降低了约束更新的计算成本。在理论方面，我们证明对于一类逐项非零效用矩阵，目标函数是强凸的，这为在线梯度下降带来了对数静态遗憾，并进一步在非精确ADMM内循环下实例化了已知的动态遗憾保证。在实验上，ASTRA在合成星座上匹配或提升了拓扑质量，并在计算时间上呈现出良好的权衡，且在部分部署和非均匀间距的现实Starlink数据上仍保持有效，而理想化结构假设在此失效。这些结果使ASTRA成为现实低地球轨道网络中高效且理论基础扎实的拓扑重构方法。
英文摘要
Dynamic topology reconfiguration is central to the reliability and efficiency of large satellite constellations, yet many existing approaches rely on idealized assumptions such as full constellation deployment or uniform orbital spacing. We present Adaptive Satellite Topology via Regret-Aware learning (ASTRA), a theoretically-grounded framework for dynamic satellite topology reconfiguration that builds on an online learning formulation and makes it computationally practical. ASTRA combines an ADMM-based offline solver with efficient online updates for both online gradient descent and online conditional gradient, yielding markedly cheaper constrained updates than generic optimization pipelines. On the theory side, we show that for a relevant class of entry-wise nonzero utility matrices, the objective is strongly convex, which yields logarithmic static regret for online gradient descent, and we further instantiate known dynamic-regret guarantees under inexact ADMM inner loops. Empirically, ASTRA matches or improves topology quality, presenting a good trade-off with computational time on synthetic constellations, and it remains effective on real Starlink data under partial deployment and non-uniform spacing, where idealized structural assumptions break down. These results position ASTRA as an efficient and theoretically grounded approach to topology reconfiguration in realistic Low Earth Orbit networks.
发表机构
- NOVA School of Science and Technology（新里斯本大学科技学院）
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