Optimization of Single-Satellite Operational Schedules Towards Enhanced Communication Capacity

There are a growing number of small satellites that are being launched and operated to accomplish novel science and technology missions. Scientists and mission operators are seeking to download large quantities of data from these small satellites, however they are resource-constrained and communicate to capacity-constrained ground networks. Motivated by the need for intelligent operational schedules for these missions, in this paper we develop an optimization formulation with the objective to maximize the data returns of a single satellite communicating to a global ground station network. We include decisions on when and how to perform satellite operations, including collecting missionspecific data by the payload and downloading data to ground stations. The formulation captures dynamic satellite states, subsystem functions, and interactions of the satellite with the external environment and ground station networks. The formulation is generic and extensible such that it is applicable to diverse mission scenarios. We apply the formulation to optimize the operations of realistic small satellite missions communicating to diverse ground networks. We demonstrate the advantages of optimizing operational schedules relative to using a conventional requirements-driven approach for operational planning. We use this formulation to perform an initial design space exploration relative to both deterministic and stochastic mission parameters.