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...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Siyuan Zhao, Jiacheng Ni, Jia Liang, Shichao Xiong, Ying Luo
Format: article
Langue:EN
Publié: MDPI AG 2021
Sujets:
synthetic aperture radar (SAR)
sparse imaging algorithm
end-to-end
deep learning
two-dimensional
Science
Q
Accès en ligne:https://doaj.org/article/1a6b2f2bb6484f92b69aa8cfa69e13cc
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!

Internet

https://doaj.org/article/1a6b2f2bb6484f92b69aa8cfa69e13cc

Documents similaires