Schedule Optimization of Imaging Missions for Multiple Satellites and Ground Stations Using Genetic Algorithm

  • Junghyun Lee
  • Heewon Kim
  • Hyun Chung
  • Haedong Kim
  • Sujin Choi
  • Okchul Jung
  • Daewon Chung
  • Kwanghee Ko
Original Paper

Abstract

In this paper, we propose a method that uses a genetic algorithm for the dynamic schedule optimization of imaging missions for multiple satellites and ground systems. In particular, the visibility conflicts of communication and mission operation using satellite resources (electric power and onboard memory) are integrated in sequence. Resource consumption and restoration are considered in the optimization process. Image acquisition is an essential part of satellite missions and is performed via a series of subtasks such as command uplink, image capturing, image storing, and image downlink. An objective function for optimization is designed to maximize the usability by considering the following components: user-assigned priority, resource consumption, and image-acquisition time. For the simulation, a series of hypothetical imaging missions are allocated to a multi-satellite control system comprising five satellites and three ground stations having S- and X-band antennas. To demonstrate the performance of the proposed method, simulations are performed via three operation modes: general, commercial, and tactical.

Keywords

Multiple satellites Mission-control systems Imaging missions Schedule optimization Genetic algorithm 

References

  1. 1.
    Lee B, Lee J, Park J, Kim H, Kim J (2003) Implementation of the mission scheduling and command planning functions for the KOMPSAT-2 mission control element. The Korean Society for Aeronautical and Space Sciences, pp 707–710Google Scholar
  2. 2.
    Jung W, Lee B, Lee S, Kim J (2006) Mission control system for KOMPSAT-2 operations, IEIC Technical Report, vol 106. Institute of Electronics, Information and Communication Engineers, pp 169–176Google Scholar
  3. 3.
    Kim H, Lee J (1998) Simulation for the mission planning of the KOMPSAT MCE. The Korean Society for Aeronautical and Space Sciences, pp 564–567Google Scholar
  4. 4.
    Lee B, Hwang Y, Kim H, Kim J (2007) Design of the flight dynamics subsystem for the COMS satellite ground control system. In: Proceedings of the third international conference on recent advances in space technologies, pp 595–601.  https://doi.org/10.1109/RAST.2007.4284063
  5. 5.
    Lee B, Jung WC, Lee S, Lee J, Kim J (2006) Design of the COMS satellite ground control system, IEIC Technical Report, vol 106. Institute of Electronics, Information and Communication Engineers, pp 35–42Google Scholar
  6. 6.
    Sule DR, Sule D (1997) Industrial scheduling, vol 20. PWS Publishing Company, New YorkMATHGoogle Scholar
  7. 7.
    Jain AS, Meeran S (1999) Deterministic job-shop scheduling: past, present and future. Eur J Oper Res 113:390–434.  https://doi.org/10.1016/S0377-2217(98)00113-1 CrossRefMATHGoogle Scholar
  8. 8.
    Spangelo S, Cutler J, Gilson K, Cohn A (2015) Optimization-based scheduling for the single-satellite, multi-ground station communication problem. Comput Oper Res 57:1–16.  https://doi.org/10.1016/j.cor.2014.11.004 MathSciNetCrossRefMATHGoogle Scholar
  9. 9.
    Rao J, Soma P, Padmashree G (1998) Multi-satellite scheduling system for LEO satellite operations. In: Proceedings of SpaceOps, TokyoGoogle Scholar
  10. 10.
    Soma P, Venkateswarlu S, Santhalakshmi S, Bagchi T, Kumar S (2004) Multi-satellite scheduling using genetic algorithms. In: Proceedings of ISTRAC/ISRO, SpaceOpsGoogle Scholar
  11. 11.
    Lee J, Kim H, Chung H, Ko K (2016) Genetic algorithm-based scheduling for ground support of multiple satellites and antennae considering operation modes. Int J Aeronaut Space Sci 17:89–100.  https://doi.org/10.5139/IJASS.2016.17.1.89 Google Scholar
  12. 12.
    Baek S, Cho K, Lee D, Kim H (2010) A comparison of scheduling optimization algorithm for the efficient satellite mission scheduling operation. The Korean Society for Aeronautical and Space Sciences, pp 48–57.  https://doi.org/10.5139/JKSAS.2010.38.1.048
  13. 13.
    Baek S, Han S, Cho K, Lee D, Yang J, Bainum PM, Kim H (2011) Development of a scheduling algorithm and GUI for autonomous satellite missions. Acta Astronaut 68:1396–1402.  https://doi.org/10.1016/j.actaastro.2010.08.011 CrossRefGoogle Scholar
  14. 14.
    Han S, Baek S, Jo S, Cho K, Lee D, Kim H (2008) Optimization of the satellite mission scheduling using genetic algorithms. The Korean Society for Aeronautical and Space Sciences, pp 1163–1170.  https://doi.org/10.5139/JKSAS.2008.36.12.1163
  15. 15.
    Lin W, Liao D (2004) A tabu search algorithm for satellite imaging scheduling. In: 2004 IEEE international conference on systems, man and cybernetics, pp 1601–1606.  https://doi.org/10.1109/ICSMC.2004.1399860
  16. 16.
    Lin W, Liao D, Liu C, Lee Y (2005) Daily imaging scheduling of an earth observation satellite. IEEE Trans Syst Hum Syst Man Cybern Part A 35:213–223.  https://doi.org/10.1109/TSMCA.2005.843380 CrossRefGoogle Scholar
  17. 17.
    Pemberton JC, Galiber F (2001) A constraint-based approach to satellite scheduling. DIMACS Ser Discret Math Theor Comput Sci 57:101–114MathSciNetCrossRefMATHGoogle Scholar
  18. 18.
    Sun B, Wang W, Qi Q (2008) Satellites scheduling algorithm based on dynamic constraint satisfaction problem. In: 2008 International conference on computer science and software engineering, pp 167–170.  https://doi.org/10.1109/CSSE.2008.577
  19. 19.
    Sun B, Wang W, Xie X, Qin Q (2010) Satellite mission scheduling based on genetic algorithm. Kybernetes 39:1255–1261.  https://doi.org/10.1108/03684921011063538 CrossRefGoogle Scholar
  20. 20.
    Tangpattanakul P, Jozefowiez N, Lopez P (2015) A multi-objective local search heuristic for scheduling earth observations taken by an agile satellite. Eur J Oper Res 245:542–554.  https://doi.org/10.1016/j.ejor.2015.03.011 MathSciNetCrossRefMATHGoogle Scholar
  21. 21.
    Dishan Q, Chuan H, Jin L, Manhao M (2013) A dynamic scheduling method of earth-observing satellites by employing rolling horizon strategy. Sci World J 2013.  https://doi.org/10.1155/2013/304047
  22. 22.
    Globus A, Crawford J, Lohn J, Pryor A (2003) Scheduling earth observing satellites with evolutionary algorithms. In: Conference on space mission challenges for information technology (SMC-IT)Google Scholar
  23. 23.
    Globus A, Crawford J, Lohn J, Pryor A (2004) A comparison of techniques for scheduling earth observing satellites. In: Proceedings of the 16th conference on innovative applications of artificial intelligence, San Jose, pp 836–843Google Scholar
  24. 24.
    Kim H, Chang YK (2015) Mission scheduling optimization of SAR satellite constellation for minimizing system response time. Aerospace Sci Technol 40:17–32.  https://doi.org/10.1016/j.ast.2014.10.006 CrossRefGoogle Scholar
  25. 25.
    Hwang FT, Yeh YY, Li SY (2010) Multi-objective optimization for multi-satellite scheduling system. In: Proceedings of Asian Association on Remote Sensing ACRS, HanoiGoogle Scholar
  26. 26.
    Frank J, Jonsson A, Morris R, Smith D (2001) Planning and scheduling for fleets of earth observing satellites. In: Proceedings of the sixth international symposium on artificial intelligence, robotics, automation and spaceGoogle Scholar
  27. 27.
    Chen Y, Zhang D, Zhou M, Zou H (2012) Multi-satellite observation scheduling algorithm based on hybrid genetic particle swarm optimization. In: Advances in information technology and industry applications. Springer, pp 441-448.  https://doi.org/10.1007/978-3-642-26001-8_58
  28. 28.
    Zhang Z, Zhang N, Feng Z (2014) Multi-satellite control resource scheduling based on ant colony optimization. Expert Syst Appl 41:2816–2823.  https://doi.org/10.1016/j.eswa.2013.10.014 CrossRefGoogle Scholar
  29. 29.
    Lee J, Wang S, Chung D, Ko K, Choi S, Ahn H, Jung O (2012) Multi-satellite control system architecture and mission scheduling optimization. In: 2012 IEEE aerospace conference, pp 1–13.  https://doi.org/10.1109/AERO.2012.6187437
  30. 30.
    Otani Y, Kohtake N, Ohkami Y (2013) Dual-use system architecture for a space situational awareness system in Japan. In: 2013 IEEE aerospace conference, pp 1–8.  https://doi.org/10.1109/AERO.2013.6496954
  31. 31.
    Boden DG, Larson WG (1996) Cost effective space mission operations. McGraw-Hill, New YorkGoogle Scholar

Copyright information

© The Korean Society for Aeronautical & Space Sciences and Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Junghyun Lee
    • 1
  • Heewon Kim
    • 2
  • Hyun Chung
    • 3
  • Haedong Kim
    • 4
  • Sujin Choi
    • 4
  • Okchul Jung
    • 4
  • Daewon Chung
    • 4
  • Kwanghee Ko
    • 5
  1. 1.Defense Agency for Technology and QualityJinjuRepublic of Korea
  2. 2.Fine Mechatronics Co., Ltd.DaeguRepublic of Korea
  3. 3.Korea Advanced Institute of Science and Technology (KAIST)DaejeonRepublic of Korea
  4. 4.Korea Aerospace Research Institute (KARI)DaejeonRepublic of Korea
  5. 5.Gwangju Institute of Science and Technology (GIST)GwangjuRepublic of Korea

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