This thesis investigates the automated tracking of particles ejected from the surface of small celestial bodies, with a particular focus on asteroid Bennu. Inspired by the obser vations from the OSIRIS-REx mission, where unexpected ejection events were captured by the spacecraft’s navigation camera, the study addresses the challenges of particle or bit reconstruction in a constrained observational environment. An extensive review of Bennu’s environment, forces acting on particles, and past research was first carried out to support a physically accurate simulation framework. Building on computer vision models and estimation techniques such as the Unscented Kalman Filter, a novel auto mated tracking algorithm was designed and tested. The algorithm was evaluated using simulations closely resembling real mission conditions, demonstrating strong performance under medium-complexity scenarios but also revealing limitations when tracking mul tiple targets under cluttered data conditions. This work lays the foundation for future development of tracking algorithms applicable to CubeSats in future exploration missions.
Questa tesi studia il tracking automatico di particelle espulse dalla superficie di piccoli corpi celesti, con particolare attenzione all’asteroide Bennu. Partendo dalle osservazioni della missione OSIRIS-REx, dove eventi di espulsione sono stati catturati dalla camera di navigazione del veicolo spaziale, lo studio affronta le sfide della ricostruzione dell’orbita delle particelle usando incompleti strumenti di ricerca. Per creare una simulazione dell’ambiente esterno fisicamente accurata è stata effettuata un’ampia revisione dell’ambiente di Bennu, delle forze che agiscono sulle particelle e delle ricerche precedenti. Basandosi su modelli di Computer Vision e tecniche di stima come l’Unscented Kalman Filter, è stato progettato e testato un nuovo algoritmo di tracking. L’algoritmo è stato testato utilizzando simulazioni che ricreano le condizioni reali della missione, dimostrando ottime prestazioni in scenari di media complessità, ma rivelando anche i limiti nell’inseguimento di bersagli multipli in condizioni di un gran number di target presenti allo stesso tempo. Questo lavoro pone le basi per lo sviluppo futuro di algoritmi di tracking ai CubeSat in future missioni di esplorazione.
Non linear multi target tracking near small celestial bodies
Marzorati, Emanuele
2024/2025
Abstract
This thesis investigates the automated tracking of particles ejected from the surface of small celestial bodies, with a particular focus on asteroid Bennu. Inspired by the obser vations from the OSIRIS-REx mission, where unexpected ejection events were captured by the spacecraft’s navigation camera, the study addresses the challenges of particle or bit reconstruction in a constrained observational environment. An extensive review of Bennu’s environment, forces acting on particles, and past research was first carried out to support a physically accurate simulation framework. Building on computer vision models and estimation techniques such as the Unscented Kalman Filter, a novel auto mated tracking algorithm was designed and tested. The algorithm was evaluated using simulations closely resembling real mission conditions, demonstrating strong performance under medium-complexity scenarios but also revealing limitations when tracking mul tiple targets under cluttered data conditions. This work lays the foundation for future development of tracking algorithms applicable to CubeSats in future exploration missions.File | Dimensione | Formato | |
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2025_07_Marzorati_Tesi.pdf
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Descrizione: Non Linear Multi Target Tracking Near Small Celestial Bodies
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https://hdl.handle.net/10589/239759