TY - GEN
T1 - A New Approach on Satellite Mission Planning with Revisiting Requirements
AU - Liu, Yuyan
AU - Li, Yuqing
AU - Liu, Pengpeng
AU - Feng, Xiaoen
AU - Jiang, Feilong
AU - Lei, Mingjia
N1 - Publisher Copyright:
© 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Genetic algorithm
KW - Population based incremental learning algorithm
KW - Revisiting requirements
KW - Satellite mission planning
UR - https://www.scopus.com/pages/publications/85103304689
U2 - 10.1007/978-3-030-69072-4_17
DO - 10.1007/978-3-030-69072-4_17
M3 - 会议稿件
AN - SCOPUS:85103304689
SN - 9783030690717
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 198
EP - 209
BT - Wireless and Satellite Systems - 11th EAI International Conference, WiSATS 2020, Proceedings
A2 - Wu, Qihui
A2 - Zhao, Kanglian
A2 - Ding, Xiaojin
PB - Springer Science and Business Media Deutschland GmbH
T2 - 11th EAI International Conference on Wireless and Satellite Systems, WiSATS 2020
Y2 - 17 September 2020 through 18 September 2020
ER -