No abstract

A graph-based network flow approach to constellation planning is presented that respects spacecraft resources and mission constraints to arrive at a preliminary operational schedule. The method discretizes task fulfillment opportunity windows into graph nodes and then adds edges based on feasibility of transition between these opportunities, either by slew maneuvers or extended-time task fulfillment during downlink operations. Intelligent graph pruning is applied to improve computation performance and provide a versatile planning capability with a minimal impact on the resulting solution. A network flow formulation allows for a simultaneous search for spacecraft plans using a Mixed Integer Linear Program (MILP). The framework enables the definition of appropriate mission constraints to ensure viability and mission efficiency among the constellation of satellites. The planning technique is demonstrated for a mission of 100 satellites to illustrate its capability and performance within this proliferated regime.