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논문 기본 정보

자료유형
학술저널
저자정보
Junghyun Lee (Gwangju Institute of Science and Technology (GIST)) Haedong Kim (Korea Aerospace Research Institute (KARI)) Hyun Chung (Korea Advanced Institute of Science and Technology (KAIST)) Kwanghee Ko (Gwangju Institute of Science and Technology (GIST))
저널정보
한국항공우주학회 International Journal of Aeronautical and Space Sciences International Journal of Aeronautical and Space Sciences Volume.17 Number.1
발행연도
2016.3
수록면
89 - 100 (12page)

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초록· 키워드

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Given the unpredictability of the space environment, satellite communications are manually performed by exchanging telecommands and telemetry. Ground support for orbiting satellites is given only during limited periods of ground antenna visibility, which can result in conflicts when multiple satellites are present. This problem can be regarded as a scheduling problem of allocating antenna support (task) to limited visibility (resource). To mitigate unforeseen errors and costs associated with manual scheduling and mission planning, we propose a novel method based on a genetic algorithm to solve the ground support problem of multiple satellites and antennae with visibility conflicts. Numerous scheduling parameters, including user priority, emergency, profit, contact interval, support time, remaining resource, are considered to provide maximum benefit to users and real applications. The modeling and formulae are developed in accordance with the characteristics of satellite communication. To validate the proposed algorithm, 20 satellites and 3 ground antennae in the Korean peninsula are assumed and modeled using the satellite tool kit (STK). The proposed algorithm is applied to two operation modes: (i) telemetry, tracking, and command and (ii) payload. The results of the present study show near-optimal scheduling in both operation modes and demonstrate the applicability of the proposed algorithm to actual mission control systems.

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Abstract
1. Introduction
2. Background
3. Scheduling considerations
4. Problem description and formulation
5. Genetic algorithm design
6. Simulation conditions
7. Results
8. Conclusion
References

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UCI(KEPA) : I410-ECN-0101-2016-558-002776152