53 Papers
196 Citations
Ling Wang is an academic researcher from Nanjing University of Aeronautics and Astronautics. The author has contributed to research in topics: Synthetic aperture radar & Radar imaging. The author has an hindex of 11, co-authored 52 publications. Previous affiliations of Ling Wang include Rensselaer Polytechnic Institute.
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Papers
Inverse Synthetic Aperture Radar Imaging Using a Fully Convolutional Neural Network
TL;DR: The proposed fully CNN (FCNN) for ISAR imaging has a multistage decomposition and multichannel filtering architecture and has no fully connected layers and can work with very few training samples as compared to existing CNN-based imaging networks.
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Bistatic Synthetic Aperture Radar imaging using ultranarrow-band continuous waveforms
Ling Wang,Birsen Yazici +1 more
- 23 May 2011
TL;DR: This work considers synthetic aperture radar system using ultra-narrowband continuous waveforms, which it refers to as Doppler Synthetic Aperture Radar (DSAR), and presents a novel image formation method for bistatic DSAR, which shows that the resolution of the image is directly related to the length of the support of the windowing function, the carrier-frequency of the transmitted waveform, and the sampling rate of the aperture.
Doppler synthetic aperture hitchhiker imaging
TL;DR: This work considers passive airborne receivers that use backscattered signals from sources of opportunity transmitting fixed-frequency waveforms, which it refers to as Doppler Synthetic Aperture Hitchhiker (DSAH), and presents a novel image formation method for DSAH, which first correlates the windowed signal obtained from one receiver with thewindowed, filtered, scaled and translated version of the received signal from another receiver.
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Sparse ISAR imaging using a greedy Kalman filtering approach
TL;DR: The Kalman filter has robust and excellent estimation performance in statistical settings for linear problems, it leads to good image reconstruction results for real ISAR data, and the images obtained by assuming the sparsity in different domains are synthesized to further improve the image reconstruction.
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Inverse Synthetic Aperture Radar Imaging Using a Deep ADMM Network
Changyu Hu,Li Ze,Ling Wang,Jun Guo,Otmar Loffeld +4 more
- 26 Jun 2019
TL;DR: Experimental results show that the proposed DAN based ISAR imaging method is superior to the existing CS method in both image reconstruction quality and computational efficiency.
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