An Optimized Method for Electromagnetic Inverse Scattering Imaging Based on GAN

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Electromagnetic Inverse scattering problem (ISP) is aimed at recontructing shapes or retrieving electromagnetic parameters of scatterers from the scattering fields. Synthetic aperture radar methods, such as Delay-and-Sum (DAS) or Delay-Multiply-and-Sum (DMAS) are often used to solve such problems. However, the imaging results are not satisfying usually. Forthermore, these methods are associated with heavy computational cost, and consequently, they are often time-consuming. In this paper, a deep learning method named pix2pix based on conditional generative adversarial network (cGAN) is applied to enhance the quarlity of imaging and reduce the time cost. The simulation results show that the proposed method can provide a new solution for the difficult ISPs.

Original languageEnglish
Title of host publicationISAPE 2024 - 14th International Symposium on Antennas, Propagation and EM Theory
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350353129
DOIs
Publication statusPublished - 2024
Event14th International Symposium on Antennas, Propagation and EM Theory, ISAPE 2024 - Hefei, China
Duration: 23 Oct 202426 Oct 2024

Publication series

NameISAPE 2024 - 14th International Symposium on Antennas, Propagation and EM Theory

Conference

Conference14th International Symposium on Antennas, Propagation and EM Theory, ISAPE 2024
Country/TerritoryChina
CityHefei
Period23/10/2426/10/24

Keywords

  • U-Net
  • conditional Generative Adversarial Networks
  • electromagnetic inverse scattering

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