3-D SAR Imaging via Perceptual Learning Framework With Adaptive Sparse Prior

Mathematically, 3-D synthetic aperture radar (SAR) imaging is a typical inverse problem, which, by nature, can be solved by applying the theory of sparse signal recovery. However, many reconstruction algorithms are constructed by exploring the inherent sparsity of imaging space, which may cause unsa...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing Jg. 61; S. 1 - 16
Hauptverfasser:	Wang, Mou, Wei, Shunjun, Shi, Jun, Zhang, Xiaoling, Guo, Yongxin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023
Schlagworte:	Algorithms Artificial neural networks Computer applications Echoes Feature extraction Image reconstruction Imaging techniques Inverse problems Iterative methods Learning Mathematical analysis Neural networks Operators (mathematics) Radar imaging Regularization SAR (radar) Signal reconstruction Synthetic aperture radar Visual perception
ISSN:	0196-2892, 1558-0644
Online-Zugang:	Volltext
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