Deep Matrix Profile for Maneuver Classification in Low Earth Orbit Satellite Trajectories - Morphologie mathématique (CMM)
Communication Dans Un Congrès Année : 2024

Deep Matrix Profile for Maneuver Classification in Low Earth Orbit Satellite Trajectories

Résumé

The characterization of satellite behavior is of paramount importance in Space Surveillance Awareness. One crucial aspect of studying satellite behavior involves the detection of out-of-station-keeping maneuvers within satellite trajectories. Since each satellite's station-keeping behavior is unique, extracting relevant information from historical data is crucial for modeling the Pattern of Life. In this context, we propose integrating a state-of-the-art data mining technique, namely the Matrix Profile, into a neural network architecture. Our approach highlights the connection with non-local models. The proposed model exhibits promising results for detecting out-of-stationkeeping maneuvers in Low Earth Orbit satellite trajectories, showcasing its effectiveness in addressing the challenges of unbalanced data.
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Dates et versions

hal-04730200 , version 1 (10-10-2024)

Identifiants

  • HAL Id : hal-04730200 , version 1

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Stéfan Baudier, Santiago Velasco-Forero, Franck Jean, Daniel Brooks, Jesus Angulo. Deep Matrix Profile for Maneuver Classification in Low Earth Orbit Satellite Trajectories. European Signal Processing Conference, 2024, IEEE, Aug 2024, Lyon, France. ⟨hal-04730200⟩
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