Ripple-Aware Cooperative Collision Avoidance for Satellite Mega-Constellations
编号:184 访问权限:仅限参会人 更新:2026-11-10 17:05:04 浏览:13次 Online

报告开始:2026年11月20日 16:30(Asia/Kolkata)

报告时间:15min

所在会场:[S3] Satellite UAV and Non-Terrestrial Networks/Networking, Security and Blockchain Systems [S3-1] Satellite UAV and Non-Terrestrial Networks/Networking, Security and Blockchain Systems

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摘要
Satellites in low Earth orbit avoid one another through small orbital adjustments. Each adjustment has an unaccounted consequence: for several hours, the public catalogue used for conjunction screening inaccurately represents the manoeuvring satellite. We quantify this inaccuracy using 620,275 public element sets covering 1,800 satellites over 120 days. manoeuvred satellite has 2.23× greater prediction error than a non-manoeuvring satellite, almost entirely along the direction of travel. Screening real orbits against stale entries produces 120 false conjunction alerts and misses 111 genuine alerts, relative to 136 genuine conjunctions. Decomposition shows that injected error increases with both manoeuvre magnitude and notification delay. Prior work addresses the former; we show that the latter dominates. For a median manoeuvre, the 3.92 h delay contributes 4.73 km of error against a 5 km alert threshold, whereas immediate notification contributes almost none. We therefore propose publishing a manoeuvre when it is planned, using the command link through which it is executed; every manoeuvrable object already has such a link. Across adoption levels, the scheme eliminates 92% of manoeuvre-induced false alarms and 96% of injected catalogue error. However, it cannot independently improve safety: a threshold rule calibrated for an uncertain catalogue responds insufficiently to an accurate one. A learned policy that observes the age of each neighbour’s data recovers this loss.
关键词
space situational awareness,Collision Avoidance,mega-constellations,multi-agent reinforcement learning,Graph Neural Networks (GNNs),conjunction screening
报告人
Rishik Bansal
Student Vellore Institute of Technology

稿件作者
Rishik Bansal Vellore Institute of Technology
Shourya Madan Vellore Institute of Technology
Arnav Sinha Vellore Institute of Technology
Karthik G M Vellore Institute of Technology
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重要日期
  • 会议日期

    11月20日

    2026

    至

    11月22日

    2026

  • 10月31日 2026

    初稿截稿日期

  • 11月07日 2026

    提前注册日期

  • 11月22日 2026

    注册截止日期

主办单位
United Societies of Science
承办单位
Pondicherry University
协办单位
IEEE Section
IEEE Madras Section
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