Autonomous operations of large-scale satellite constellations and ground station networks

A dynamic optimization problem is employed to aid operators o f large-scale satellite constellations with automated mission planning and data collection. Traditional techniques focus on graph-theoretic ideas that use heuristics to simplify the problem. The solution presented in this paper is formulated as a dynamic optimization problem that scales linearly as the number of satellites and ground stations increases. The problem formulation is implemented with the DIDO (c) pseudospectral optimal control solver to produce deconflicted ground antenna slew trajectories as a function ofparameters and constraints used commonly by satellite operators. In this paper, one such factor, space-to-ground link margin. is used for the proofofconcept. Other parameters can include mission priority, asset availability, and onboard spacecraft health. The specific problem solved here is to optimally slew ground-based antennas between multiple satellites that are simultaneously in view of one or more earth stations. The approach is tested using orbiting CubeSats and the Mobile CubeSat Command and Control (MC3) network