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