Agile Satellite Mission Planning via Task Clustering and Double-Layer Tabu Algorithm
Satellite observation schedule is investigated in this paper. A mission planning algorithm of task clustering is proposed to improve the observation efficiency of agile satellite. The newly developed method can make the satellite observe more targets and therefore save observation resources. First,...
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| Published in: | Computer modeling in engineering & sciences Vol. 122; no. 1; pp. 235 - 257 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Henderson
Tech Science Press
01.01.2020
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| Subjects: | |
| ISSN: | 1526-1492, 1526-1506, 1526-1506 |
| Online Access: | Get full text |
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| Summary: | Satellite observation schedule is investigated in this paper. A mission planning algorithm of task clustering is proposed to improve the observation efficiency of agile satellite. The newly developed method can make the satellite observe more targets and therefore save observation resources.
First, for the densely distributed target points, a preprocessing scheme based on task clustering is proposed. The target points are clustered according to the distance condition. Second, the local observation path is generated by Tabu algorithm in the inner layer of cluster regions. Third,
considering the scatter and cluster sets, the global observation path is obtained by adopting Tabu algorithm in the outer layer. Simulation results show that the algorithm can effectively reduce the task planning time of large-scale point targets while ensuring the optimal solution quality. |
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| Bibliography: | 1526-1492(20200115)122:1L.235;1- ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1526-1492 1526-1506 1526-1506 |
| DOI: | 10.32604/cmes.2020.08070 |