Mixed integer (non)linear approaches for the satellite constellation design problem

In this paper, we propose mathematical optimization models to solve the satellite constellation design problem for discontinuous coverage. In such a design problem, the aim is to determine the minimal number of satellites (and, incidentally, their 3D placements) in order to observe a fixed Earth reg...

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Bibliographic Details
Published in:Optimization and engineering Vol. 24; no. 4; pp. 2299 - 2320
Main Authors: Mencarelli, Luca, Floquet, Julien, Georges, Frédéric, Grenier, Dominique
Format: Journal Article
Language:English
Published: New York Springer US 01.12.2023
Springer Verlag
Subjects:
Computer Science
Control
Engineering
Environmental Management
Financial Engineering
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Research Article
Systems Theory
Discontinuous coverage
Satellite constellation design
Revisiting time
Mixed integer nonlinear and linear programming
DISCONTINUOUS COVERAGE
SATELLITE CONSTELLATION DESIGN
REVISITING TIME
MIXED INTEGER NONLINEAR AND LINEAR PROGRAMMING
ISSN:1389-4420, 1573-2924
Online Access:Get full text
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Summary:In this paper, we propose mathematical optimization models to solve the satellite constellation design problem for discontinuous coverage. In such a design problem, the aim is to determine the minimal number of satellites (and, incidentally, their 3D placements) in order to observe a fixed Earth region within a given revisiting time. Two Mixed Integer Nonlinear formulations are introduced. The first one is a feasibility problem based on the direct mathematical definition of pixel observability. The second one consists in introducing a set of indicator variables which specify if a satellite observes a pixel at a given time-stamp. In order to obtain a linear problem, the possible positions of the satellites are discretized. Finally, computational results show the potential and limitations of the proposed approaches.
ISSN:1389-4420
1573-2924
DOI:10.1007/s11081-022-09774-9