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Open AccessArticle

Multipath Ghost Suppression Based on Generative Adversarial Nets in Through-Wall Radar Imaging

1
College of Information Science & Technology, Chengdu University of Technology, Chengdu 610059, China
2
School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
*
Author to whom correspondence should be addressed.
Electronics 2019, 8(6), 626; https://doi.org/10.3390/electronics8060626
Received: 21 April 2019 / Revised: 17 May 2019 / Accepted: 31 May 2019 / Published: 3 June 2019
In this paper, we propose an approach that uses generative adversarial nets (GAN) to eliminate multipath ghosts with respect to through-wall radar imaging (TWRI). The applied GAN is composed of two adversarial networks, namely generator G and discriminator D. Generator G learns the spatial characteristics of an input radar image to construct a mapping from an input to output image with suppressed ghosts. Discriminator D evaluates the difference (namely, the residual multipath ghosts) between the output image and the ground-truth image without multipath ghosts. On the one hand, by training G, the image difference is gradually diminished. In other words, multipath ghosts are increasingly suppressed in the output image of G. On the other hand, D is trained to improve in evaluating the diminishing difference accompanied with multipath ghosts as much as possible. These two networks, G and D, fight with each other until G eliminates the multipath ghosts. The simulation results demonstrate that GAN can effectively eliminate multipath ghosts in TWRI. A comparison of different methods demonstrates the superiority of the proposed method, such as the exemption of prior wall information, no target images with degradation, and robustness for different scenes. View Full-Text
Keywords: generative adversarial nets; through-wall radar imaging; multipath ghost suppression; generator and discriminator generative adversarial nets; through-wall radar imaging; multipath ghost suppression; generator and discriminator
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Jia, Y.; Song, R.; Chen, S.; Wang, G.; Guo, Y.; Zhong, X.; Cui, G. Multipath Ghost Suppression Based on Generative Adversarial Nets in Through-Wall Radar Imaging. Electronics 2019, 8, 626.

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