End-to-End SAR Deep Learning Imaging Method Based on Sparse Optimization

End-to-End SAR Deep Learning Imaging Method Based on Sparse Optimization

Synthetic aperture radar (SAR) imaging has developed rapidly in recent years. Although the traditional sparse optimization imaging algorithm has achieved effective results, its shortcomings are slow imaging speed, large number of parameters, and high computational complexity. To solve the above prob...

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Autores principales: Siyuan Zhao, Jiacheng Ni, Jia Liang, Shichao Xiong, Ying Luo
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
synthetic aperture radar (SAR)
sparse imaging algorithm
end-to-end
deep learning
two-dimensional
Science
Q
Acceso en línea:https://doaj.org/article/1a6b2f2bb6484f92b69aa8cfa69e13cc
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