公开星链卫星机动行为数据集，助力轨道安全研究
SpaceTrack-TimeSeries: Time Series Dataset towards Satellite Orbit Analysis
- 融合TLE与高精度星历数据，构建真实轨道行为数据集
- 涵盖星链卫星机动行为，支持碰撞风险评估与检测方法验证
- 适合航天器轨道分析、空间交通管理领域研究人员使用
随着航空航天技术快速发展及低地球轨道（LEO）卫星星座的大规模部署，天文观测与深空探测面临的挑战日益突出。对高精度空间物体轨道数据——包括卫星定位、星座构型及深空卫星动力学的全面分析需求愈发迫切。然而，公开可获取的真实世界数据集仍严重不足，难以支撑空间物体机动行为预测与碰撞风险评估等研究。本文通过收集并整理星链卫星的典型机动行为数据，构建了一个代表性数据集。该数据集融合了两行元素（TLE）目录数据与对应的高精度星历数据，实现了对空间物体行为更真实、多维度的建模，为机动检测方法的实际部署和日益拥挤轨道环境中的碰撞风险评估提供了重要支持。
原文摘要 · Abstract (English)
With the rapid advancement of aerospace technology and the large-scale deployment of low Earth orbit (LEO) satellite constellations, the challenges facing astronomical observations and deep space exploration have become increasingly pronounced. As a result, the demand for high-precision orbital data on space objects-along with comprehensive analyses of satellite positioning, constellation configurations, and deep space satellite dynamics-has grown more urgent. However, there remains a notable lack of publicly accessible, real-world datasets to support research in areas such as space object maneuver behavior prediction and collision risk assessment. This study seeks to address this gap by collecting and curating a representative dataset of maneuvering behavior from Starlink satellites. The dataset integrates Two-Line Element (TLE) catalog data with corresponding high-precision ephemeris data, thereby enabling a more realistic and multidimensional modeling of space object behavior. It provides valuable insights into practical deployment of maneuver detection methods and the evaluation of collision risks in increasingly congested orbital environments.
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