An Application of Online Learning to Spacecraft Memory Dump Optimization

With the fast-growing number of satellites orbiting Earth, the Space Operations field has become a prominent and thriving sector. As a consequence, the complexity of planning satellite operations is constantly increasing: Ground Stations have to handle communication with multiple satellites simultaneously while frequently engaged in Launch and Early Orbit Phase (LEOP) activities; Satellite Operators need to perform routine tasks and promptly react to contingencies while checking the status of the incoming and disseminated satellite's products. These actions are costly, require time, and are remarkably prone to human errors. Despite this, Satellite Operators still carry out many of these duties by relying on their technical expertise rather than leveraging modern machine learning tools. On the other hand, computers, hardware, and flight software are becoming more sophisticated with each passing day.