Synthetic Dataset of Maneuvering Low Earth Orbit Satellite Trajectories for AI Analysis - Morphologie mathématique (CMM)
Communication Dans Un Congrès Année : 2024

Synthetic Dataset of Maneuvering Low Earth Orbit Satellite Trajectories for AI Analysis

Résumé

The characterization of satellite behavior is of paramount importance in Space Surveillance Awareness. It involves modeling complex patterns from large operational databases, making AI tools well-suited to handle this use case. Despite existing contributions, no database is dedicated to Pattern-of-Life study in the Low Earth Orbit regime. In this context, we provide a dataset of satellite trajectories, focusing on station-keeping issues. The proposed database contains generated trajectories based on real data. Our experiments on the provided dataset and real trajectories tend to verify the representativity of the data and highlight the complexity of the Pattern-of-Life related tasks.
Fichier principal
Vignette du fichier
Synthetic_Dataset_of_Maneuvering_Low_Earth_Orbit_Satellite_Trajectories_for_AI_Analysis.pdf (978.58 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04755327 , version 1 (27-10-2024)

Identifiants

  • HAL Id : hal-04755327 , version 1

Citer

Stéfan Baudier, Santiago Velasco-Forero, Franck Jean, Daniel Brooks, Jesus Angulo. Synthetic Dataset of Maneuvering Low Earth Orbit Satellite Trajectories for AI Analysis. Proceedings of SPAICE2024 : The First Joint European Space Agency / IAA Conference on AI in and for Space, Sep 2024, Oxfordshire, United Kingdom. ⟨hal-04755327⟩
15 Consultations
10 Téléchargements

Partager

More