Scheduling Multiple Agile Earth Observation Satellites for Oversubscribed Targets Using Complex Networks Theory
Autor: | Rui Zhang, Yi Gu, Xinwei Wang, Chao Han |
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Rok vydání: | 2019 |
Předmět: |
021103 operations research
General Computer Science Job shop scheduling Discretization business.industry Computer science Distributed computing 0211 other engineering and technologies General Engineering complex networks 02 engineering and technology Complex network Earth observation satellite Scheduling (computing) feedback heuristic multiple observations 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering business lcsh:TK1-9971 Agile earth observation satellites Agile software development |
Zdroj: | IEEE Access, Vol 7, Pp 110605-110615 (2019) |
ISSN: | 2169-3536 |
DOI: | 10.1109/access.2019.2925704 |
Popis: | The earth observation satellites (EOSs) scheduling is of great importance to achieve efficient observation missions. The agile EOSs (AEOS) with a stronger attitude maneuvering capacity can greatly improve observation efficiency while increasing scheduling complexity. Meanwhile, multiple observation requirements for the same ground target, which the existing models and methods cannot completely satisfy, are raised to accomplish scientific projects. In order to fill in this gap, the multiple AEOSs scheduling model for oversubscribed targets with multiple observations is initially developed, and the potential observation missions attained by available time windows discretization are regarded as nodes in the complex networks. To solve the multiple-observation AEOS scheduling problem, an improved feedback structured heuristic is designed by defining the node and target importance factors. On the basis of a real world Chinese AEOS constellation, simulation experiments are conducted to validate the heuristic's efficiency in comparison with a constructive algorithm and a structured genetic algorithm. |
Databáze: | OpenAIRE |
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