한국군사과학기술학회지 (Journal of the Korea Institute of Military Science and Technology)

  • 제24권1호
  • /
  • Pages.12-21
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  • 2021
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  • 1598-9127(pISSN)
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  • 2636-0640(eISSN)
한국군사과학기술학회 (The Korea Institute of Military Science and Technology)
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Conditional GAN을 이용한 SAR 표적영상의 해상도 변환

Resolution Conversion of SAR Target Images Using Conditional GAN

  • 박지훈 (국방과학연구소 제3기술연구본부) ;
  • 서승모 (국방과학연구소 제3기술연구본부) ;
  • 최여름 (국방과학연구소 제3기술연구본부) ;
  • 유지희 (국방과학연구소 제3기술연구본부)
  • Park, Ji-Hoon (The 3rd Research and Development Institute, Agency for Defense Development) ;
  • Seo, Seung-Mo (The 3rd Research and Development Institute, Agency for Defense Development) ;
  • Choi, Yeo-Reum (The 3rd Research and Development Institute, Agency for Defense Development) ;
  • Yoo, Ji Hee (The 3rd Research and Development Institute, Agency for Defense Development)
  • 투고 : 2020.07.27
  • 심사 : 2020.11.06
  • 발행 : 2021.02.05
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초록

For successful automatic target recognition(ATR) with synthetic aperture radar(SAR) imagery, SAR target images of the database should have the identical or highly similar resolution with those collected from SAR sensors. However, it is time-consuming or infeasible to construct the multiple databases with different resolutions depending on the operating SAR system. In this paper, an approach for resolution conversion of SAR target images is proposed based on conditional generative adversarial network(cGAN). First, a number of pairs consisting of SAR target images with two different resolutions are obtained via SAR simulation and then used to train the cGAN model. Finally, the model generates the SAR target image whose resolution is converted from the original one. The similarity analysis is performed to validate reliability of the generated images. The cGAN model is further applied to measured MSTAR SAR target images in order to estimate its potential for real application.

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참고문헌

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