Objective task matching strategy for Multi-Satellite Imaging Mission Planning in complex heterogeneous scenarios
Authors: 
Xueying Yang, Min Hu, Gang HuangAuthors Info & Claims
Pages 96 - 101
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.
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- Objective task matching strategy for Multi-Satellite Imaging Mission Planning in complex heterogeneous scenarios
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Published In
December 2023
109 pages
ISBN:9798400709258
DOI:10.1145/3638264
Copyright © 2023 ACM.
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Published: 29 January 2024
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- National Natural Science Foundation of China
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MICML 2023
MICML 2023: 2023 International Conference on Mathematics, Intelligent Computing and Machine Learning
December 15 - 17, 2023
Chengdu, China
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