Multi-Sensor Tasking for Ground-Based Space Situational Awareness via Job-Shop Scheduling Problem
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Shimane, Yuri
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Abstract
Sensor-tasking to collect observation measurements of resident space objects constitutes a central problem for Space Situational Awareness (SSA). One specific type of sensor-tasking problem aims at rapidly producing an optimal or near-optimal schedule spanning over an observation horizon of a few hours up to a few nights. We derive tractable binary linear program formulations for solving the scheduling problem for both single and multiple telescopes. Observations are modeled by assuming the telescopes must track orbit passes for a user-defined exposure time. The proposed programs are efficiently solvable by branch-and-bound algorithms for instance sizes of practical applicability.
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2025
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