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Objective task matching strategy for Multi-Satellite Imaging Mission Planning in complex heterogeneous scenarios

Published: 29 January 2024 Publication History

Abstract

Complex heterogeneous scenarios with multiple mission requirement relationships, poor model scalability, resource conflicts during mission planning are the serious challenges currently facing the field of multi-satellite imaging mission planning (MSIMP). To solve this difficult problem, this paper proposes an Objective task-matching strategy and Improved adaptive differential evolution algorithm (OTMS-IADE). Firstly, the target task matching strategy for MSIMP in complex heterogeneous scenarios is constructed for multi-user, multi-satellite and multi-task situations, which overcomes the problem of poor scalability of the planning model in complex heterogeneous scenarios, and reduces the loss of resources caused by inappropriate task allocation; Secondly, to address the problem of low execution efficiency and long planning time due to large MSIMP solution space and complex constraints in complex heterogeneous scenarios, an improved adaptive differential evolution algorithm is proposed to reasonably trade-off the spatial search performance and the spatial exploitation performance to enhance the algorithm solution efficiency. Simulation experiments show that the OTMS-IADE algorithm for processing complex heterogeneous scenarios MSIMP has obvious advantages regarding task importance optimization and timeliness.

References

[1]
Atul Adya, Paramvir Bahl, Jitendra Padhye, Alec Wolman, and Lidong Zhou. 2004. A multi-radio unification protocol for IEEE 802.11 wireless networks. In Proceedings of the IEEE 1st International Conference on Broadnets Networks (BroadNets’04) . IEEE, Los Alamitos, CA, 210–217. https://doi.org/10.1109/BROADNETS.2004.8
[2]
Qiu, W.; Xu, C.; Ren, Z.; Teo, K.L. Scheduling and Planning Framework for Time Delay Integration Imaging by Agile Satellite. IEEE Trans. Aerosp. Electron. Syst. 2022, 58, 189–205.
[3]
G. Zhang, X. Li, G. Hu, Z. Zhang, J. An, W. Man, Mission Planning Issues of Imaging Satellites: Summary, Discussion, and Prospects, Int. J. Aerosp. Eng. 2021 (2021) 1–20. https://doi.org/10.1155/2021/7819105
[4]
Y. Song, J. Ou, J. Wu, Y. Wu, L. Xing, and Y. Chen, “A cluster-based genetic optimization method for satellite range scheduling system,” Swarm Evol. Comput., vol. 79, no. 4, p. 101316, Jun. 2023.
[5]
X. Han, M. Yang, S. Wang, and T. Chao, “Continuous monitoring scheduling for moving targets by Earth observation satellites,” Aerosp. Sci. Technol., vol. 140, no. 4, p. 108422, Sep. 2023.
[6]
Q. Qu, K. Liu, X. Li, Y. Zhou, and J. Lu, “Satellite Observation and Data-Transmission Scheduling using Imitation Learning based on Mixed Integer Linear Programming,” IEEE Trans. Aerosp. Electron. Syst., vol. 140, no. 4, pp. 1–25, Sep. 2022.
[7]
Y. Yu, Q. Hou, J. Zhang, and W. Zhang, “Mission scheduling optimization of multi-optical satellites for multi-aerial targets staring surveillance,” J. Franklin Inst., vol. 357, no. 13, pp. 8657–8677, Sep. 2020.
[8]
C. Li, W. Xu, L. Xu, and Y. Wang, “An approach to multi-satellite TT&C resource scheduling based on multi-agent technology and comprehensive weighted priority determination method,” J. Phys. Conf. Ser., vol. 1812, no. 1, p. 012001, Feb. 2021.
[9]
J. Liang, Y. Zhu, Y. Luo, J. Zhang, H. Zhu, A precedence-rule-based heuristic for satellite onboard activity planning, Acta Astronaut. 178 (2021) 757–772. https://doi.org/10.1016/j.actaastro.2020.10.020
[10]
W. Zhu, X. Hu, W. Xia, and H. Sun, “A three-phase solution method for the scheduling problem of using earth observation satellites to observe polygon requests,” Comput. Ind. Eng., vol. 130, no. 1, pp. 97–107, Apr. 2019.
[11]
C. Han, Y. Gu, G. Wu, and X. Wang, “Simulated Annealing-Based Heuristic for Multiple Agile Satellites Scheduling Under Cloud Coverage Uncertainty,” IEEE Trans. Syst. Man, Cybern. Syst., vol. 53, no. 5, pp. 2863–2874, May 2023.
[12]
T. Wang, Q. Luo, L. Zhou, and G. Wu, “Space division and adaptive selection strategy based differential evolution algorithm for multi-objective satellite range scheduling problem,” Swarm Evol. Comput., vol. 83, no. 5, p. 101396, Dec. 2023.
[13]
Z. E., R. Shi, L. Gan, H. Baoyin, and J. Li, “Multi-satellites imaging scheduling using individual reconfiguration based integer coding genetic algorithm,” Acta Astronaut., vol. 178, no. 5, pp. 645–657, Jan. 2021.
[14]
J. Liang, Y. Zhu, Y. Luo, J. Zhang, and H. Zhu, “A precedence-rule-based heuristic for satellite onboard activity planning,” Acta Astronaut., vol. 178, no. 5, pp. 757–772, Jan. 2021.
[15]
M. Ghasemi, M. Zare, P. Trojovský, A. Zahedibialvaei, and E. Trojovská, “A hybridizing-enhanced differential evolution for optimization,” PeerJ Comput. Sci., vol. 9, no. 5, p. e1420, Jun. 2023.
[16]
H. Zhang, J. Sun, K. C. Tan, and Z. Xu, “Learning Adaptive Differential Evolution by Natural Evolution Strategies,” IEEE Trans. Emerg. Top. Comput. Intell., vol. 7, no. 3, pp. 872–886, Jun. 2023.
[17]
J.-Y. Li, K.-J. Du, Z.-H. Zhan, H. Wang, and J. Zhang, “Distributed Differential Evolution With Adaptive Resource Allocation,” IEEE Trans. Cybern., vol. 53, no. 5, pp. 2791–2804, May 2023.

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  • (2024)Tracking Moving Targets by Earth Observation Satellites: A Multi-Objective Scheduling Approach2024 International Conference on New Trends in Computational Intelligence (NTCI)10.1109/NTCI64025.2024.10776156(37-41)Online publication date: 18-Oct-2024

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            MICML '23: Proceedings of the 2023 International Conference on Mathematics, Intelligent Computing and Machine Learning
            December 2023
            109 pages
            ISBN:9798400709258
            DOI:10.1145/3638264
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            Published: 29 January 2024

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            Author Tags

            1. Adaptive differential evolution algorithm
            2. Multi-Satellite Imaging Mission Planning
            3. Objective task matching strategy

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            • National Natural Science Foundation of China

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            • (2024)Tracking Moving Targets by Earth Observation Satellites: A Multi-Objective Scheduling Approach2024 International Conference on New Trends in Computational Intelligence (NTCI)10.1109/NTCI64025.2024.10776156(37-41)Online publication date: 18-Oct-2024

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