Agile Satellite Mission Planning for Moving Targets Observation Based on Modified Genetic Algorithm

This paper predicts the location of moving targets and proposes a mission planning method for multiple Agile Earth Observation Satellites (AEOSs) based on modified genetic algorithm. Firstly, the task areas are gridded, and the location of moving targets are predicted through the combination of Baye...

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Bibliographic Details
Published inChinese Control Conference pp. 2001 - 2006
Main Authors Qi, Maochen, Guo, Wenting, Liu, Zhengyang, Guo, Yanning
Format Conference Proceeding
LanguageEnglish
Published Technical Committee on Control Theory, Chinese Association of Automation 28.07.2025
Subjects
Agile earth observation satellite
Bayes methods
Costs
Earth
Genetic algorithms
Image resolution
Imaging
Linear programming
Mission planning
Modified genetic algorithm
Moving target
Planning
Satellites
Time-frequency analysis
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ISSN1934-1768
DOI10.23919/CCC64809.2025.11178330

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Summary:This paper predicts the location of moving targets and proposes a mission planning method for multiple Agile Earth Observation Satellites (AEOSs) based on modified genetic algorithm. Firstly, the task areas are gridded, and the location of moving targets are predicted through the combination of Bayesian inference and the target transition probability matrix. A multisatellite mission planning model is established by considering the active push-broom imaging characteristics of AEOS. Then, an objective function considering the observation profit and attitude maneuver cost is designed, and the observation sequence is solved by a modified genetic algorithm. Meanwhile, a conflict resolution algorithm based on observation frequency and observation time window dispersion is proposed. Finally, the experimental results are provided to verify the effectiveness of the proposed method.
ISSN:1934-1768
DOI:10.23919/CCC64809.2025.11178330