32 citations · 47 across the 12 of their papers we have counts for
12 papers
Shadow-Oriented Tracking Method for Multi-Target Tracking in Video-SAR
Xiaochuan Ni, Xiaoling Zhang, Xu Zhan +4
This work focuses on multi-target tracking in Video synthetic aperture radar. Specifically, we refer to tracking based on targets' shadows. Current methods have limited accuracy as…
A Model-data-driven Network Embedding Multidimensional Features for Tomographic SAR Imaging
Yu Ren, Xiaoling Zhang, Xu Zhan +3
Deep learning (DL)-based tomographic SAR imaging algorithms are gradually being studied. Typically, they use an unfolding network to mimic the iterative calculation of the classica…
Near-filed SAR Image Restoration with Deep Learning Inverse Technique: A Preliminary Study
Xu Zhan, Xiaoling Zhang, Wensi Zhang +3
Benefiting from a relatively larger aperture's angle, and in combination with a wide transmitting bandwidth, near-field synthetic aperture radar (SAR) provides a high-resolution im…
Solving 3D Radar Imaging Inverse Problems with a Multi-cognition Task-oriented Framework
Xu Zhan, Xiaoling Zhang, Mou Wang +3
This work focuses on 3D Radar imaging inverse problems. Current methods obtain undifferentiated results that suffer task-depended information retrieval loss and thus don't meet the…
Constant-Time-Delay Interferences In Near-Field SAR: Analysis And Suppression In Image Domain
Xu Zhan, Xiaoling Zhang, Jun Shi +1
Inevitable interferences exist for the SAR system, adversely affecting the imaging quality. However, current analysis and suppression methods mainly focus on the far-field situatio…
AETomo-Net: A Novel Deep Learning Network for Tomographic SAR Imaging Based on Multi-dimensional Features
Yu Ren, Xiaoling Zhang, Yunqiao Hu +1
Tomographic synthetic aperture radar (TomoSAR) imaging algorithms based on deep learning can effectively reduce computational costs. The idea of existing researches is to reconstru…
3D Super-Resolution Imaging Method for Distributed Millimeter-wave Automotive Radar System
Yanqin Xu, Xiaoling Zhang, Shunjun Wei +3
Millimeter-wave (mmW) radar is widely applied to advanced autopilot assistance systems. However, its small antenna aperture causes a low imaging resolution. In this paper, a new di…
Near-Field SAR Image Restoration Based On Two Dimensional Spatial-Variant Deconvolution
Wensi Zhang, Xiaoling Zhang, Xu Zhan +3
Images of near-field SAR contains spatial-variant sidelobes and clutter, subduing the image quality. Current image restoration methods are only suitable for small observation angle…
Sar Ship Detection based on Swin Transformer and Feature Enhancement Feature Pyramid Network
Xiao Ke, Xiaoling Zhang, Tianwen Zhang +2
With the booming of Convolutional Neural Networks (CNNs), CNNs such as VGG-16 and ResNet-50 widely serve as backbone in SAR ship detection. However, CNN based backbone is hard to m…
Two Dimensional Sparse-Regularization-Based InSAR Imaging with Back-Projection Embedding
Xu Zhan, Xiaoling Zhang, Shunjun Wei +1
Interferometric Synthetic Aperture Radar (InSAR) Imaging methods are usually based on algorithms of match-filtering type, without considering the scene's characteristic, which caus…
Shadow-Background-Noise 3D Spatial Decomposition Using Sparse Low-Rank Gaussian Properties for Video-SAR Moving Target Shadow Enhancement
Xiaowo Xu, Xiaoling Zhang, Tianwen Zhang +3
Moving target shadows among video synthetic aperture radar (Video-SAR) images are always interfered by low scattering backgrounds and cluttered noises, causing poor detec-tion-trac…
Balance Scene Learning Mechanism for Offshore and Inshore Ship Detection in SAR Images
Tianwen Zhang, Xiaoling Zhang, Jun Shi +5
Huge imbalance of different scenes' sample numbers seriously reduces Synthetic Aperture Radar (SAR) ship detection accuracy. Thus, to solve this problem, this letter proposes a Bal…