Concurrent Optimization of Satellite Phasing and Tasking for Cislunar Space Situational Awareness

Recently, renewed interest in cislunar space spurred by private and public organizations has driven research for future infrastructure in the region. As Earth–Moon traffic increases amidst a growing space economy, monitoring architectures supporting this traffic must also develop. These are likely to be realized as constellations of patrol satellites surveying traffic between the Earth and the Moon. This work investigates the concurrent optimization of patrol satellite phasing and tasking to provide information-maximal traffic coverage in periodic orbits. The core contribution is a formulation that defines and solves an optimization problem. We cast the problem as an optimization program with an “outer loop” that solves the phasing problem and an “inner loop” that solves the tasking problem. We analyze two such objectives and present a trio of algorithms for optimization. We present case studies outlining the efficacy of our solution methods, sensitivity to constellation dynamics, and a contrastive analysis of policy behavior with choice of objective.