most citedAETomo-Net: A Novel Deep Learning Network for Tomographic SAR Imaging Based on Multi-dimensional Features

6 citations · 15 across the 11 of their papers we have counts for

collaborators
Showing eess.SPShow all

7 papers · 1 filter

eess.SP2022

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…

eess.SP2022

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…

eess.SP20224 cited

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…

eess.SP20226 cited

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…

eess.SP20221 cited

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…

eess.SP20221 cited

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…