24 citations · 43 across the 9 of their papers we have counts for
6 papers · 1 filter
CVGG-Net: Ship Recognition for SAR Images Based on Complex-Valued Convolutional Neural Network
Dandan Zhao, Zhe Zhang, Dongdong Lu +3
Ship target recognition is a vital task in synthetic aperture radar (SAR) imaging applications. Although convolutional neural networks have been successfully employed for SAR image…
SPHR-SAR-Net: Superpixel High-resolution SAR Imaging Network Based on Nonlocal Total Variation
Guoru Zhou, Zhongqiu Xu, Yizhe Fan +5
High-resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering propert…
MF-JMoDL-Net: A Deep Network for Azimuth Undersampling Pattern Design and Ambiguity Suppression for Sparse SAR Imaging
Yuwei Wu, Zhe Zhang, Xiaolan Qiu +2
repetition frequency (PRF). Given the system complexity and resource constraints, it is often difficult to achieve high imaging performance and low ambiguity without compromising t…
ATASI-Net: An Efficient Sparse Reconstruction Network for Tomographic SAR Imaging with Adaptive Threshold
Muhan Wang, Zhe Zhang, Xiaolan Qiu +2
Tomographic SAR technique has attracted remarkable interest for its ability of three-dimensional resolving along the elevation direction via a stack of SAR images collected from di…
TomoSAR-ALISTA: Efficient TomoSAR Imaging via Deep Unfolded Network
Muhan Wang, Zhe Zhang, Yue Wang +2
Synthetic aperture radar (SAR) tomography (TomoSAR) has attracted remarkable interest for its ability in achieving three-dimensional reconstruction along the elevation direction fr…
A Novel Gradient Descent Least Squares (GDLS) Algorithm for Efficient SMV Gridless Line Spectrum Estimation with Applications in Tomographic SAR Imaging
Ruizhe Shi, Zhe Zhang, Xiaolan Qiu +1
This paper presents a novel efficient method for gridless line spectrum estimation problem with single snapshot, namely the gradient descent least squares (GDLS) method. Convention…