Cislunar Space Situational Awareness Constellation Design and Planning with Facility Location Problem

TL;DR

This paper introduces a MILP-based approach for designing cislunar space situational awareness constellations, optimizing satellite placement and sensor tasking to improve coverage and monitoring capabilities in the Earth-Moon system.

Contribution

It presents a novel integrated formulation and a Lagrangian solution method for the joint constellation design and sensor placement in cislunar space.

Findings

Efficient assessment of near-optimal CSSA constellations.

Demonstrated coverage of the cislunar Cone of Shame.

Validated approach for monitoring low-energy transfers in Earth-Moon L2 region.

Abstract

Driven by the surmounting interest for dedicated infrastructure in cislunar space, this work considers the satellite constellation design for cislunar space situational awareness (CSSA). We propose a mixed-integer linear programming (MILP)-based formulation that simultaneously tackles the constellation design and sensor-tasking subproblems surrounding CSSA. Our approach generates constellation designs that provide coverage with considerations for the field-of-view of observers. We propose a time-expanded p-Median problem (TE-p-MP) which considers the optimal placement of p space-based observers into discretized locations based on orbital slots along libration point orbits, simultaneously with observer pointing directions across discretized time. We further develop a Lagrangian method for the TE-p-MP, where a relaxed problem with an analytical solution is derived, and customized heuristics leveraging the orbital structure of candidate observer locations are devised. The performance of the proposed formulation is demonstrated with several case studies for CSSA constellations monitoring the cislunar Cone of Shame and a periodic time-varying transit window for low-energy transfers located in the Earth-Moon L2 neck region. The proposed problem formulation, along with the Lagrangian method, is demonstrated to enable a fast assessment of near-optimal CSSA constellations, equipping decision-makers with a critical technique for exploring the design trade space.