Volume 39 Issue 4
Jul.  2019
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Article Navigation >  Chinese Journal of Space Science  > 2019  >  39(4): 494-501
YU Yanjun, WANG Feng, MIAO Yue. Optimal Design of Constellation Configuration for Irregular Imaging Area Coverage Based on Improved Simulated Annealing Algorithm[J]. Chinese Journal of Space Science, 2019, 39(4): 494-501. doi: 10.11728/cjss2019.04.494
Citation: YU Yanjun, WANG Feng, MIAO Yue. Optimal Design of Constellation Configuration for Irregular Imaging Area Coverage Based on Improved Simulated Annealing Algorithm[J]. Chinese Journal of Space Science, 2019, 39(4): 494-501. doi: 10.11728/cjss2019.04.494
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Optimal Design of Constellation Configuration for Irregular Imaging Area Coverage Based on Improved Simulated Annealing Algorithm

doi: 10.11728/cjss2019.04.494

  • School of Astronautics, Harbin Institute of Technology, Harbin 150009

  • Received Date: 2018-07-02
  • Rev Recd Date: 2019-03-29
  • Publish Date: 2019-07-15
    Abstract
  • The requirements of Earth observation through satellites is increasing in recent years. An optimization design method of constellation configuration for irregular imaging area coverage is proposed. For a single point target, an improved simulated annealing algorithm is used for constellations configuration design which can satisfy the revisiting time requirement. The optimizing objectives are minimum number of satellites and the requirement of revisiting time. In order to meet the requirements of observing a large and irregular shape area using less satellites and with a specific revisiting time, a new algorithm which is based on the equal-area grid point coverage method as well as the improved simulated annealing algorithm is proposed. The new algorithm can be used to optimize the constellation configuration and realize imaging irregular area targets with full coverage. The influence of target illumination condition is analyzed. A comparison is made between the optimal results ignoring illumination and with illumination. Taking some specific area as examples, the simulations are performed to prove the feasibility of the algorithm. The results show that the optimal constellation configuration for the designated area with certain constraints can be obtained by using the algorithm.

     

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