Multiobjective Optimization Design of TomoSAR Satellite Orbit Based on Multireference Transfer Orbit
Publication: Journal of Aerospace Engineering
Volume 35, Issue 5
Abstract
This paper investigates an optimal orbit design method for single-satellite synthetic aperture radar tomography (TomoSAR) missions. Satellites require multibaseline observations for three-dimensional imaging. Thus, we need to weigh performance indicators such as global coverage, sampling rate, fuel consumption, and revisit accuracy. Considering these performance indicators, this paper proposes a multiobjective optimization algorithm based on multireference transfer orbit (M-RTO), which demonstrates superiority in fuel consumption. Fuel consumption is the primary optimization objective as it determines the lifetime of the satellite. First, we use Pareto optimization for the objectives of revisit time and fuel consumption. Then, we adopt an adaptive hybrid genetic algorithm (AHGA) for the objectives of revisit accuracy and fuel consumption. Numerical simulation verifies that compared with the single-reference transfer orbit method, the multireference transfer orbit method decreases fuel consumption by , and the rest of the performance indicators meet the mission requirements.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors are grateful for the support provided for this study by the National Natural Science Foundation of China (Nos. 11502142 and 61703276).
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Published In
Journal of Aerospace Engineering
Volume 35 • Issue 5 • September 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Oct 12, 2021
Accepted: May 13, 2022
Published online: Jul 13, 2022
Published in print: Sep 1, 2022
Discussion open until: Dec 13, 2022
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