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A Genetic Algorithm for Designing Triplet LEO Satellite Constellation with Three Adjacent Satellites

  • Saeid KohaniEmail author
  • Peng Zong
Original Paper
  • 1 Downloads

Abstract

Genetic algorithm can be applied in the optimization design of satellite constellation, which is imperative in various fields such as communication, surveillance and navigation. Opposite goals, such as optimizing performance and reducing the number of satellites in constellations along with low cost of construction and launch, have been analyzed in this paper. This paper focuses on a suitable and lucrative method for designing a conceptual model of satellite constellation using the GA method. There are many options that could be chosen as an acceptable solution to implement LEO satellite constellations with some adjacent satellites on different orbits. Each option should be an accurate assessment based on various indicators such as mass, reliability, cost and technology constraint (complexity). Important constraints including the number of satellites, orbit planes, etc., are discussed. A triplet LEO constellation with three adjacent satellites on different orbits is proposed by considering coverage capability and precession. For regional coverage of the area on Earth, a special genetic algorithm model is designed for Leo triplet constellations. The optimal solution can enhance the capability of communication and navigation intensively. The performance of proposed algorithm is corroborated by the simulation results and indicates that it is feasible and effective.

Keywords

Triplet constellation LEO satellite coverage Orbit Genetic algorithm Assessment costing trade off 

Notes

References

  1. 1.
    Liu G (2003) Research on the key technologies of networking in the NGSO satellite mobile communication system. University of Electronic Science and Technology of China, Chengdu, p 12Google Scholar
  2. 2.
    Curry GR (1996) A low-cost space-based radar system concept. Sept, IEEE AES Magaz, pp 21–24Google Scholar
  3. 3.
    Whelan DA, Filip A, Koss JJ et al (2000) Global space-based ground surveillance mission utility and performance of Discoverer II. IEEE aerospace conference proceedings pp 1–I1Google Scholar
  4. 4.
    Tollefson MV, Preiss BK (1998) Space based radar constellation optimization. IEEE aerospace conference, pp 379–388Google Scholar
  5. 5.
    Budianto LA, Olds JR (2000) A collaborative optimization approach to design and deployment of a space based infrared system constellation.In: IEEE NAECON, pp 385–393Google Scholar
  6. 6.
    Li SD, Zhu J, Li GX (2005) Optimization of LEO regional communication satellite constellation with GA algorithm. J Commun 26:122–128Google Scholar
  7. 7.
    Circi C, Ortore E, Bunkheila F (2014) Satellite constellations in sliding ground track orbits. Aerosp Sci Technol 39(8):395–402CrossRefGoogle Scholar
  8. 8.
    Bai HF, Ren X, Xi XN (1999) The orbit models for designing LEO satellite constellations. J Natl Univ Defense Technol 21:1–4Google Scholar
  9. 9.
    Lee S, Wu Y, Mortari D (2015) Satellite constellation design for telecommunication in Antarctica. Int J Satell Commun Netw.  https://doi.org/10.1002/sat.1128 Google Scholar
  10. 10.
    Wertz JR (2009) Orbit & constellation design & management. Hawthorne, ch 9 and ch 13. Microcosm, Springer Press, New YorkGoogle Scholar
  11. 11.
    Liu SK, Liu HD (2014) Constellation design and performance simulation of LEO satellite communication system. GNSS World China 39:19–23Google Scholar
  12. 12.
    Wertz JR, Larson JR (1999) Space mission analysis and design, 3rd edn. Microcosm, TorranceGoogle Scholar
  13. 13.
    Galati G (1996) Spaced-based SSR constellation for global air traffic control. In: IEEE, Trans. AES-32, no. 3, p1088 1106Google Scholar
  14. 14.
    Frayssinhes E, Espace A (1996) Investigating new satellite constellation geometries with genetic algorithms. In: AIAA-96-3636-CPGoogle Scholar
  15. 15.
    Biria AD, Marchand BG (2014) Constellation design for space-based space situational awareness applications: an analytical approach. J Spacecr Rockets.  https://doi.org/10.2514/1.a32622 Google Scholar
  16. 16.
    Fakoor Mahdi, Bakhtiari Majid, Soleymani Mahshid (2016) Optimal design of the satellite constellation arrangement reconfiguration process. Adv Space Res 58(3):372–386CrossRefGoogle Scholar
  17. 17.
    Lansard E, Frayssinhes E, Palmade JL (1996) Global design of satellite constellations: a multi-criteria performance comparison of classical walker patterns and new design patterns. IAF-96 A.1.02, 47th international astronautical congress. Beijing (7–11 Oct. 1996) Google Scholar
  18. 18.
    Dufour F, Lasserre E, Brousse P (1999) A multistage approach to design and optimize a communication satellite constellation. In: IAF-99-A.2.09, 50th international astronautical congress. Amsterdam (4–8 Oct. 1999) Google Scholar
  19. 19.
    Chen R (2004) Design and Analysis of non-geostationary orbit communication system. Modem science technology of telecommunications. J Electron Inf Technol 2004(1):40–44 (in chinese) MathSciNetGoogle Scholar
  20. 20.
    Mason W, Coverstone-Carroll V, Hartmann J (1998) Optimal earth orbiting satellite constellations via a Pareto Genetic Algorithm. In: AIAA/AAS astrodynamics specialist conference and exhibit.  https://doi.org/10.2514/6.1998-4381
  21. 21.
    Orbit Design for Ground Surveillance Using Genetic Algorithms (2006) Ossama Omarabdelkhalik, Daniele Mortari. Journal of Guidance, Control, and Dynamics 29:1231–1235.  https://doi.org/10.2514/1.16722 CrossRefGoogle Scholar
  22. 22.
    Marcus ML, Sedwick RJ (2017) Low earth orbit Debris removal technology assessment using genetic algorithms. J Spacecr Rockets 54:1110–1126.  https://doi.org/10.2514/1.a33671 CrossRefGoogle Scholar

Copyright information

© The Korean Society for Aeronautical & Space Sciences 2019

Authors and Affiliations

  1. 1.Astronautics CollegeNanjing University of Aeronautics and AstronauticsNanjingChina

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