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Open AccessArticle

Optimization of Reconfigurable Satellite Constellations Using Simulated Annealing and Genetic Algorithm

1
Materials R&D Center, Samsung SDI, Gyeonggi-do 16678, Korea
2
Center for Electronic Materials, Korea Institute of Science and Technology, Seoul 02792, Korea
3
Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(4), 765; https://doi.org/10.3390/s19040765
Received: 19 November 2018 / Revised: 6 February 2019 / Accepted: 9 February 2019 / Published: 13 February 2019
(This article belongs to the Special Issue Satellite and Airborne Remote Sensing for Earth Monitoring)
Agile Earth observation can be achieved with responsiveness in satellite launches, sensor pointing, or orbit reconfiguration. This study presents a framework for designing reconfigurable satellite constellations capable of both regular Earth observation and disaster monitoring. These observation modes are termed global observation mode and regional observation mode, constituting a reconfigurable satellite constellation (ReCon). Systems engineering approaches are employed to formulate this multidisciplinary problem of co-optimizing satellite design and orbits. Two heuristic methods, simulated annealing (SA) and genetic algorithm (GA), are widely used for discrete combinatorial problems and therefore used in this study to benchmark against a gradient-based method. Point-based SA performed similar or slightly better than the gradient-based method, whereas population-based GA outperformed the other two. The resultant ReCon satellite design is physically feasible and offers performance-to-cost(mass) superior to static constellations. Ongoing research on observation scheduling and constellation management will extend the ReCon applications to radar imaging and radio occultation beyond visible wavelengths and nearby spectrums. View Full-Text
Keywords: Earth observation; remote sensing; satellite constellation; reconfigurability; repeat ground tracks; simulated annealing; genetic algorithm Earth observation; remote sensing; satellite constellation; reconfigurability; repeat ground tracks; simulated annealing; genetic algorithm
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Paek, S.W.; Kim, S.; de Weck, O. Optimization of Reconfigurable Satellite Constellations Using Simulated Annealing and Genetic Algorithm. Sensors 2019, 19, 765.

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