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Wireless and Satellite Systems. 11th EAI International Conference, WiSATS 2020, Nanjing, China, September 17-18, 2020, Proceedings, Part II

Research Article

A New Approach on Satellite Mission Planning with Revisiting Requirements

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  • @INPROCEEDINGS{10.1007/978-3-030-69072-4_17,
        author={Yuyan Liu and Yuqing Li and Pengpeng Liu and Xiaoen Feng and Feilong Jiang and Mingjia Lei},
        title={A New Approach on Satellite Mission Planning with Revisiting Requirements},
        proceedings={Wireless and Satellite Systems. 11th EAI International Conference, WiSATS 2020, Nanjing, China, September 17-18, 2020, Proceedings, Part II},
        proceedings_a={WISATS PART 2},
        year={2021},
        month={2},
        keywords={Satellite mission planning Revisiting requirements Population based incremental learning algorithm Genetic algorithm},
        doi={10.1007/978-3-030-69072-4_17}
    }
    
  • Yuyan Liu
    Yuqing Li
    Pengpeng Liu
    Xiaoen Feng
    Feilong Jiang
    Mingjia Lei
    Year: 2021
    A New Approach on Satellite Mission Planning with Revisiting Requirements
    WISATS PART 2
    Springer
    DOI: 10.1007/978-3-030-69072-4_17
Yuyan Liu1, Yuqing Li1,*, Pengpeng Liu2, Xiaoen Feng1, Feilong Jiang1, Mingjia Lei1
  • 1: Harbin Institute of Technology
  • 2: Naval Research Academy
*Contact email: bradley@hit.edu.cn

Abstract

With the development of space science and technology, the demand of observation mission increases. However, due to the limitations of the performance of platform or payloads and space environment of the remote sensing satellite, the observation ability is restricted, so it is necessary to carry out the mission planning. Aiming at the observation task of revisiting hot spots by remote sensing satellite, this paper firstly analyzes the practical constraints, and designs several functions about optimization targets. Secondly, the mathematical model was established. Thirdly, the algorithm to solve the problem was based on PBIL. Finally, to examine the performance of the algorithm, this paper creates simulation scenarios and test cases by means of STK, and obtains the initial simulation time window sequence. By comparing with the results of genetic algorithm, the effectiveness of the algorithm in solving the problem of multi-satellite revisit mission planning has been verified, which is better than the results of genetic algorithm.

Keywords
Satellite mission planning Revisiting requirements Population based incremental learning algorithm Genetic algorithm
Published
2021-02-28
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-69072-4_17
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