利用自然轨道进动的漂移感知多目标空间拖船物流
Drift-Aware Multi-Target Space Tug Logistics Using Natural Orbital Precession
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中文总结 AI 辅助
针对多目标空间拖船物流中轨道平面方向不同致推进剂成本高的问题，提出漂移感知轨迹优化框架，通过增强漂移轨道、全局时间预算优化器和序列恢复测试等方法，实现与基准成本高匹配度及快速在轨重规划。
中文摘要 AI 辅助
多交会任务在目标轨道平面方向不同时推进剂成本高昂，传统任务设计将地球扁率引起的交点进动视为需消除的扰动。本文提出漂移感知轨迹优化框架，将进动用作任务设计资源，并与欧空局凯斯勒运行轨迹优化竞赛的获奖方案对比。贡献如下：一是增强漂移轨道调整中间轨道参数；二是全局单段时间预算优化器解决时间分配与下游交点几何耦合；三是序列恢复测试重推清除顺序。应用该框架在竞赛转移时间规则下与基准成本匹配度高，算法支持错过机动后的快速在轨重新规划。
英文摘要
Multi-rendezvous missions for active debris removal and in-orbit servicing incur prohibitive propellant costs when their targets differ in the orientation of their orbital planes, and classical mission design treats the nodal precession induced by Earth's oblateness as a perturbation to be cancelled. This paper presents a drift-aware trajectory optimisation framework that instead exploits that precession as a mission-design resource, benchmarked against the published winning solution to the European Space Agency's Kessler Run trajectory-optimisation competition as a trusted reference. Three methodological contributions are made. First, an enhanced drift orbit shapes the size, shape, and inclination of an intermediate orbit to tune the differential precession rate, substantially cheaper than the altitude-only designs of prior work in the Sun-synchronous regime, where inclination is the dominant lever. Second, a global per-leg time-budget optimiser makes explicit and resolves the coupling between drift-time allocation and downstream nodal geometry that defeats greedy allocation. Third, a sequence-recovery test independently re-derives a removal order consistent with the published reference from the debris catalogue alone. Applied to the full debris campaign on the published mission partition under the competition's transfer-time rules, the framework closely matches the published benchmark cost using only analytical transfer models and minutes of single-core computation. A cross-validation anchored to a widely used flight-dynamics tool quantifies the fidelity limits of the analytic model and bounds the cost of literal execution, and the constructive nature of the algorithm supports rapid in-orbit replanning after a missed manoeuvre.
