Agile Earth Observation Satellite Scheduling Algorithm for Emergency Tasks Based on Multiple Strategies

Sun, Haoyu; Wei, Xiaoying; Wang, Zhilong; Hu, Xiaoxuan

doi:10.1007/s11518-021-5506-4

Cited by 11 publications

(1 citation statement)

References 34 publications

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“…Their research sheds new light on how to optimize the emergency mission-oriented earth satellite observation orbit maneuvering problem in three dimensions: optimal response time, ground resolution, and fuel consumption. Sun et al [24] established an emergency task planning model and proposed a multi-strategy differential evolution algorithm based on the time window segmentation method to solve the problem.…”

Section: Introductionmentioning

confidence: 99%

A Unified Model for Multi-Satellite Imaging Mission Planning in Various Scenarios

Yang

Zhang

et al. 2023

IEEE Access

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Multi-satellite imaging mission planning (MSIMP) has been difficult in various scenarios due to the complex constraints of multi-satellite imaging, the wide area covered by target points, and the difficulty of achieving different mission requirements in a short period of time with limited satellite resources. In addressing this challenge, this work investigates multi-satellite imaging mission planning based on the Unified Plan Model and Improved Adaptive Differential Evolution algorithm (UPM-IADE). First, a unified model is built based on two scenarios: a large-scale imaging mission and an emergency support mission, and then a mission assignment framework is adaptively selected based on mission priority. Second, a monorail task synthesis method based on visible time windows is created to clarify the execution relationship between the satellite and the target point. Finally, an individual weight ranking rule is developed, and the weight is used to combine the fitness value ranking and diversity ranking into a final fitness value ranking, which is used to select individuals that satisfy the mutation requirements into the mutation strategy pool for adaptive mutation strategy selection. Experiments 1, 2, 3, and 4 have demonstrated that UPM-IADE can successfully resolve the imaging satellite mission planning for both scenarios while providing remarkable performance in terms of high mission benefit and rapid response.INDEX TERMS Multi-satellite imaging mission planning, global large-scale imaging mission, emergency support mission, adaptive differential evolution algorithm, individual weight ranking rule.

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Section: Introductionmentioning

confidence: 99%

A Unified Model for Multi-Satellite Imaging Mission Planning in Various Scenarios

Yang

Zhang

et al. 2023

IEEE Access

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An Adaptive Local Grid Nesting-based Genetic Algorithm for Multi-earth Observation Satellites’ Area Target Observation

Xing,

Xia,

et al. 2024

J. Syst. Sci. Syst. Eng.

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A discrete teaching–learning based optimization algorithm with local search for rescue task allocation and scheduling

2023

Applied Soft Computing

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Agile Earth Observation Satellite Scheduling Algorithm for Emergency Tasks Based on Multiple Strategies

Cited by 11 publications

References 34 publications

A Unified Model for Multi-Satellite Imaging Mission Planning in Various Scenarios

A Unified Model for Multi-Satellite Imaging Mission Planning in Various Scenarios

An Adaptive Local Grid Nesting-based Genetic Algorithm for Multi-earth Observation Satellites’ Area Target Observation

A discrete teaching–learning based optimization algorithm with local search for rescue task allocation and scheduling

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