Automatic target recognition on synthetic aperture radar imagery: A survey

O Kechagias-Stamatis, N Aouf - IEEE Aerospace and Electronic …, 2021 - ieeexplore.ieee.org
Automatic target recognition (ATR) for military applications is one of the core processes
toward enhancing intelligence and autonomously operating military platforms. Spurred by …

A survey on the applications of convolutional neural networks for synthetic aperture radar: Recent advances

AH Oveis, E Giusti, S Ghio… - IEEE Aerospace and …, 2021 - ieeexplore.ieee.org
In recent years, convolutional neural networks (CNNs) have drawn considerable attention
for the analysis of synthetic aperture radar (SAR) data. In this study, major subareas of SAR …

Sparse synthetic aperture radar imaging from compressed sensing and machine learning: Theories, applications, and trends

G Xu, B Zhang, H Yu, J Chen, M **ng… - IEEE Geoscience and …, 2022 - ieeexplore.ieee.org
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 …

FEC: A feature fusion framework for SAR target recognition based on electromagnetic scattering features and deep CNN features

J Zhang, M **ng, Y **e - IEEE Transactions on Geoscience and …, 2020 - ieeexplore.ieee.org
The active recognition of interesting targets has been a vital issue for synthetic aperture
radar (SAR) systems. The SAR recognition methods are mainly grouped as follows …

Mixed loss graph attention network for few-shot SAR target classification

M Yang, X Bai, L Wang, F Zhou - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Restricted by the observation condition, synthetic aperture radar (SAR) automatic target
classification based on deep learning usually suffers from insufficient training samples. To …

Multilevel scattering center and deep feature fusion learning framework for SAR target recognition

Z Liu, L Wang, Z Wen, K Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In synthetic aperture radar (SAR) automatic target recognition (ATR), there are mainly two
types of methods: the physics-driven model and the data-driven network. The physics-driven …

Fusion recognition of space targets with micromotion

X Tian, X Bai, R Xue, R Qin… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
During the observation of micromotion targets in space, inverse synthetic aperture radar
usually obtains the narrowband and wideband echoes simultaneously. In order to exploit …

Target recognition in SAR images by deep learning with training data augmentation

Z Geng, Y Xu, BN Wang, X Yu, DY Zhu, G Zhang - Sensors, 2023 - mdpi.com
Mass production of high-quality synthetic SAR training imagery is essential for boosting the
performance of deep-learning (DL)-based SAR automatic target recognition (ATR) …

A comprehensive survey of machine learning applied to radar signal processing

P Lang, X Fu, M Martorella, J Dong, R Qin… - arxiv preprint arxiv …, 2020 - arxiv.org
Modern radar systems have high requirements in terms of accuracy, robustness and real-
time capability when operating on increasingly complex electromagnetic environments …

Spatial–temporal ensemble convolution for sequence SAR target classification

R Xue, X Bai, F Zhou - IEEE Transactions on Geoscience and …, 2020 - ieeexplore.ieee.org
Although numerous methods based on sequence image classification have improved the
accuracy of synthetic-aperture radar (SAR) automatic target recognition, most of them only …