Satellite Constellation Configuration Design Optimization

Design an optimal satellite constellation configuration using mixed-integer linear programs with coverage as the figure of merit.

This repository contains the MATLAB code used in our paper, "Optimal Satellite Constellation Configuration Design: A Collection of Mixed Integer Linear Programs," published in the Journal of Spacecraft and Rockets.

The goal of the programs presented in this paper is to design provably optimal satellite constellation configurations by determining the optimal number of satellites and their distributions, subject to physical and operational constraints imposed in a given mission context. The coverage metrics considered are percentage coverage, average revisit time, and maximum revisit time.

This MATLAB File Exchange version complements our GitHub repository by providing a separate, MATLAB-friendly implementation using Live Scripts with detailed comments for readability and ease of use.

Available Programs

• Set Covering Location Problem (SCLP): Minimize constellation configuration cost subject to complex spatiotemporal coverage requirements.
• Partial Set Covering Location Problem (PSCLP): Minimize constellation configuration cost subject to a percentage coverage requirement.
• Maximal Covering Location Problem (MCLP): Maximize observation rewards for a fixed number of satellites.
• Minimal Maximum Revisit Time (MMRT): Minimize the maximum revisit time for a fixed number of satellites.
• Minimal Average Revisit Time (MART): Minimize the average revisit time for a fixed number of satellites.

Directory Structure

• main.mlx: Contains the main code in which the user specifies the input parameters and program and retrieves the optimal constellation configuration and its coverage timeline.
• sclp.mlx, psclp.mlx, mclp.mlx, mmrt.mlx, and mart.mlx: Contain the individual programs.

Requirements

• YAMILP R20250626

Optional

• A commercial optimization solver, such as Gurobi Optimizer