RESOURCE-CONSTRAINED AUTONOMOUS OPERATIONS OF SATELLITE CONSTELLATIONS AND GROUND STATION NETWORKS

Abstract

To address the growing population of small satellite constellations that rely on distributed ground station networks, a dynamic optimization problem is formulated and solved. Specifically, this dissertation addresses the problem formulation, algorithm implementation, and experimental techniques developed to optimally slew ground-based antennas between multiple satellites that are simultaneously in view of one or more earth stations. The problem is solved using DIDO, a MATLAB optimal control solver, to produce deconflicted ground antenna slew trajectories. The deconfliction parameters include space-to-ground link budgets, mission priority, asset availability, and onboard health. Traditional methods employ heuristics to generate a subset of available targets and a separate process to check feasibility of the solution. The method described in this dissertation deterministically solves the problem in a single step. The approach is experimentally validated and tested using a small constellation of low-Earth-orbiting CubeSats operated by the Small Satellite Laboratory at the Naval Postgraduate School, using the Mobile CubeSat Command and Control (MC3) ground station network.