Sparse synthetic aperture radar imaging from compressed sensing and machine learning: Theories, applications, and trends
Synthetic aperture radar (SAR) image formation can be treated as a class of ill-posed linear
inverse problems, and the resolution is limited by the data bandwidth for traditional imaging …
inverse problems, and the resolution is limited by the data bandwidth for traditional imaging …
TPSSI-Net: Fast and enhanced two-path iterative network for 3D SAR sparse imaging
The emerging field of combining compressed sensing (CS) and three-dimensional synthetic
aperture radar (3D SAR) imaging has shown significant potential to reduce sampling rate …
aperture radar (3D SAR) imaging has shown significant potential to reduce sampling rate …
SAE-Net: A deep neural network for SAR autofocus
W Pu - IEEE Transactions on Geoscience and Remote …, 2022 - ieeexplore.ieee.org
The sparsity-driven technique is a widely used tool to solve the synthetic aperture radar
(SAR) imaging problem. However, it always encounters sensitivity to motion errors. To solve …
(SAR) imaging problem. However, it always encounters sensitivity to motion errors. To solve …
Sparse logistic regression based one-bit sar imaging
S Ge, D Feng, S Song, J Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
One-bit synthetic aperture radar (SAR) imaging has garnered significant interest due to its
ability to lower the cost of storing enormous amounts of data during sampling and …
ability to lower the cost of storing enormous amounts of data during sampling and …
3DRIED: A high-resolution 3-D millimeter-wave radar dataset dedicated to imaging and evaluation
Millimeter-wave (MMW) 3-D imaging technology is becoming a research hotspot in the field
of safety inspection, intelligent driving, etc., due to its all-day, all-weather, high-resolution …
of safety inspection, intelligent driving, etc., due to its all-day, all-weather, high-resolution …
γ-Net: Superresolving SAR tomographic inversion via deep learning
Synthetic aperture radar tomography (TomoSAR) has been extensively employed in 3-D
reconstruction in dense urban areas using high-resolution SAR acquisitions. Compressive …
reconstruction in dense urban areas using high-resolution SAR acquisitions. Compressive …
Holographic imaging with XL-MIMO and RIS: Illumination and reflection design
This paper addresses a near-field imaging problem utilizing extremely large-scale multiple-
input multiple-output (XL-MIMO) antennas and reconfigurable intelligent surfaces (RISs) …
input multiple-output (XL-MIMO) antennas and reconfigurable intelligent surfaces (RISs) …
Lightweight FISTA-inspired sparse reconstruction network for mmW 3-D holography
Integrating compressed sensing (CS) with millimeter-wave (mmW) holography has shown
great potential to achieve lightweight onboard hardware, low sampling ratio, and high-speed …
great potential to achieve lightweight onboard hardware, low sampling ratio, and high-speed …
Efficient ADMM framework based on functional measurement model for mmW 3-D SAR imaging
Compressed sensing (CS) shows significant potential in the field of active millimeter-wave
(mmW) synthetic aperture radar (SAR) imaging due to the merits of reducing system …
(mmW) synthetic aperture radar (SAR) imaging due to the merits of reducing system …
SAF-3DNet: Unsupervised AMP-inspired network for 3-D MMW SAR imaging and autofocusing
Z Zhou, S Wei, H Zhang, R Shen… - … on Geoscience and …, 2022 - ieeexplore.ieee.org
The sparse imaging method based on compressed sensing (CS) is widely used in the field
of millimeter-wave (MMW) synthetic aperture radar (SAR) imaging. However, 3-D sparse …
of millimeter-wave (MMW) synthetic aperture radar (SAR) imaging. However, 3-D sparse …