发表机构
Stanford University; Kayhan Space（斯坦福大学; Kayhan空间公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出贝叶斯连续模型预测控制（BC-MPC），通过漏检后更新轨道信念并重规划天线指向，在保持基线扫描可行性的同时优化搜索，相比沿轨扫描在模拟和真实数据中显著提高航天器获取概率。
AI 中文摘要
本文介绍了贝叶斯连续模型预测控制（BC-MPC），这是一种自适应方法，在继续可行的基线扫描的同时重新规划近期天线指向，用于在发射后立即寻找并建立与航天器的联系，此时其真实位置最不确定。分离后，发射和部署误差可能使航天器偏离预测位置足够远，以至于操作员必须在地面联系期间主动搜索以建立通信。每次漏检都会提供关于哪些轨道假设仍然合理的信息，但搜索不确定区域的一部分可能会消耗到达另一部分所需的时间。BC-MPC在漏检后更新基于粒子的轨道信念，并在保持可行性的同时重新规划天线指向引导。其连续性有助于保留未来搜索覆盖范围，而贪婪和短视方法可能会为了即时获取收益而牺牲这些覆盖范围。我们将BC-MPC与操作上普遍采用的沿轨扫描和其他搜索算法在常见的搜索时间预算、初始不确定性和天线约束下进行比较。在96次具有匹配不确定性的模拟部署中，BC-MPC比沿轨扫描提高了获取概率，并减少了受限的平均获取时间。我们还使用来自Transporter-16拼车发射的83艘航天器的发射前、发射后和初始获取星历对该方法进行了评估。使用部署前或部署后的两行轨道要素（TLEs）进行规划，在通常假设的不确定性模型下，BC-MPC将建模的获取概率比沿轨扫描提高了约12个百分点。
英文摘要
This paper introduces Bayesian Continuation Model Predictive Control (BC-MPC), an adaptive method that replans near-term antenna pointings while continuing a feasible baseline sweep, for finding and establishing contact with spacecraft immediately after launch when their true positions are most uncertain. After separation, launch and deployment errors can leave the spacecraft sufficiently far from its predicted position that operators must actively search for it during ground contacts to establish communications. Each missed detection provides information about which orbital hypotheses remain plausible, but searching one part of the uncertainty region can consume the time needed to reach another. BC-MPC updates a particle-based orbital belief after missed detections and replans antenna pointing guidance while retaining feasibility. Its continuation helps preserve future search coverage that greedy and short-horizon methods can sacrifice for immediate acquisition gains. We compare BC-MPC against the operationally prevalent along-track sweep and additional search algorithms under common search-time budgets, initial uncertainty, and antenna constraints. Across 96 simulated deployments with matched uncertainty, BC-MPC improves acquisition probability over the along-track sweep and reduces restricted mean acquisition time. We additionally evaluate the method using pre-launch, post-launch, and initial acquisition ephemerides for 83 spacecraft from the Transporter-16 rideshare launch. Using either pre-deployment or post-deployment two-line element sets (TLEs) for planning, BC-MPC improves modeled acquisition probability over the along-track sweep by approximately 12 percentage points under the commonly assumed uncertainty model.
Comments9 pages, 9 figures, 4 tables
