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 …
RMIST-Net: Joint range migration and sparse reconstruction network for 3-D mmW imaging
Compressed sensing (CS) demonstrates significant potential to improve image quality in 3-
D millimeter-wave imaging compared with conventional matched filtering (MF). However …
D millimeter-wave imaging compared with conventional matched filtering (MF). However …
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 …
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 …
Learning-based split unfolding framework for 3-D mmW radar sparse imaging
The application of the compressed sensing (CS) method in the radar field enables the radar
imaging system to satisfy both low data cost and high reconstruction quality; however, it is …
imaging system to satisfy both low data cost and high reconstruction quality; however, it is …
3-D SAR data-driven imaging via learned low-rank and sparse priors
In the research topic of three-dimensional (3-D) synthetic aperture radar (SAR) imaging, the
sparsity-enforcing techniques offer promise in shortening the sensing time and improving …
sparsity-enforcing techniques offer promise in shortening the sensing time and improving …
Holographic SAR tomography image reconstruction by combination of adaptive imaging and sparse Bayesian inference
In this letter, we propose an imaging algorithm for the holographic synthetic aperture radar
tomography in the circumstance of sparse and nonuniform elevation circular passes …
tomography in the circumstance of sparse and nonuniform elevation circular passes …
CTV-Net: Complex-valued TV-driven network with nested topology for 3-D SAR imaging
The regularization-based approaches offer promise in improving synthetic aperture radar
(SAR) imaging quality while reducing system complexity. However, the widely applied …
(SAR) imaging quality while reducing system complexity. However, the widely applied …
MDLI-Net: Model-driven learning imaging network for high-resolution microwave imaging with large rotating angle and sparse sampling
Microwave imaging with large rotating angle and sparse sampling is an attractive approach
to obtain the high-resolution target image with reduced radar resource. However, the …
to obtain the high-resolution target image with reduced radar resource. However, the …
Multiscale 3-d–2-d mixed cnn and lightweight attention-free transformer for hyperspectral and lidar classification
The effective combination of hyperspectral image (HSI) and light detection and ranging
(LiDAR) data can be used for land cover classification. Recently, deep-learning-based …
(LiDAR) data can be used for land cover classification. Recently, deep-learning-based …