SpaceTrack-TimeSeries: Time Series Dataset towards Satellite Orbit Analysis
This addresses the urgent need for high-precision orbital data to support research in space object maneuver prediction and collision risk assessment, particularly for astronomical observations and deep space exploration, but it is incremental as it focuses on dataset creation rather than new methods.
The study tackled the lack of public datasets for satellite orbit analysis by collecting and curating a dataset of maneuvering behavior from Starlink satellites, integrating TLE catalog and high-precision ephemeris data to enable realistic modeling of space object behavior.
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.