AF-AMPNet: A deep learning approach for sparse aperture ISAR imaging and autofocusing
Inverse synthetic aperture radar (ISAR) imaging and autofocusing are challenging under
sparse aperture (SA) conditions. Traditional imaging or autofocusing methods fail to obtain …
sparse aperture (SA) conditions. Traditional imaging or autofocusing methods fail to obtain …
SAR image reconstruction via incremental imaging with compressive sensing
For synthetic aperture radar (SAR) imaging, the irregular loss of received data and the
nonuniformly under sampling yield the SAR azimuth ambiguity (SAA) resulting in the …
nonuniformly under sampling yield the SAR azimuth ambiguity (SAA) resulting in the …
Ground moving target imaging based on compressive sensing framework with single-channel SAR
MS Kang, KT Kim - IEEE Sensors Journal, 2019 - ieeexplore.ieee.org
Ground moving target imaging (GMTIm) is considered one of the most important applications
of synthetic aperture radar (SAR). Phase modulation from a moving target's higher-order …
of synthetic aperture radar (SAR). Phase modulation from a moving target's higher-order …
Sar image change detection via multiple-window processing with structural similarity
In this paper, a synthetic aperture radar (SAR) change detection approach is proposed
based on a structural similarity index measure (SSIM) and multiple-window processing …
based on a structural similarity index measure (SSIM) and multiple-window processing …
Semi-supervised DEGAN for optical high-resolution remote sensing image scene classification
Semi-supervised methods have made remarkable achievements via utilizing unlabeled
samples for optical high-resolution remote sensing scene classification. However, the …
samples for optical high-resolution remote sensing scene classification. However, the …
[HTML][HTML] Displacement prediction for long-span bridges via limited remote sensing images: An adaptive ensemble regression method
Spaceborne remote sensing via synthetic aperture radar (SAR) images offers promising
solutions to long-term structural health monitoring by providing local displacement time …
solutions to long-term structural health monitoring by providing local displacement time …
Automatic SAR image registration via Tsallis entropy and iterative search process
MS Kang, KT Kim - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) image registration is a process of geometrically aligning two
or more remote sensing images, acquired at different times, from different viewpoints or from …
or more remote sensing images, acquired at different times, from different viewpoints or from …
Compressive synthetic aperture radar imaging and autofocusing by augmented Lagrangian methods
We consider the problem of synthetic aperture radar (SAR) image reconstruction from
undersampled data in the presence of phase errors. We formulate the problem as one of …
undersampled data in the presence of phase errors. We formulate the problem as one of …
Robust SAR Automatic Target Recognition Based on Transferred MS‐CNN with L2‐Regularization
Y Zhai, W Deng, Y Xu, Q Ke, J Gan… - Computational …, 2019 - Wiley Online Library
Though Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) via
Convolutional Neural Networks (CNNs) has made huge progress toward deep learning …
Convolutional Neural Networks (CNNs) has made huge progress toward deep learning …
End-to-end SAR deep learning imaging method based on sparse optimization
S Zhao, J Ni, J Liang, S Xiong, Y Luo - Remote Sensing, 2021 - mdpi.com
Synthetic aperture radar (SAR) imaging has developed rapidly in recent years. Although the
traditional sparse optimization imaging algorithm has achieved effective results, its …
traditional sparse optimization imaging algorithm has achieved effective results, its …