한국전자파학회논문지 (The Journal of Korean Institute of Electromagnetic Engineering and Science)

  • 제19권3호
  • /
  • Pages.294-303
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  • 2008
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  • 1226-3133(pISSN)
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  • 2288-226X(eISSN)
한국전자파학회 (The Korean Institute of Electromagnetic Engineering and Science)
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표적 구분을 위한 ISAR 영상 기법에 대한 연구

A Study on ISAR Imaging Algorithm for Radar Target Recognition

  • Park, Jong-Il (Department of Electronic Engineering, Yeungnam University) ;
  • Kim, Kyung-Tae (Department of Electronic Engineering, Yeungnam University)
  • 발행 : 2008.03.31
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⟨ 이전 논문 다음 논문 ⟩

초록

ISAR(Inverse Synthetic Aperture Radar) 영상은 표적에 대한 RCS(Radar Cross Section)를 2차원 공간에 표현하며, 표적구분에 이용될 수 있다. 2차원 IFFT(Inverse fast Fourier Transform)를 이용하여 쉽고 빠르게 ISAR 영상을 만들 수 있다. 하지만 IFFT를 이용하여 만든 ISAR 영상은 측정된 주파수 대역 폭과 각도 영역이 작아질 경우 해상도가 떨어지게 된다. 이를 해결하기 위해 AR(Auto Regressive), MUSIC(Multiple SIgnal Classification), Modified MUSIC과 같은 고해상도 스펙트럼 예측 기법을 이용하여 주파수 대역 폭과 각도 영역이 작아도 높은 해상도의 ISAR 영상을 만들 수 있다. 본 논문에서는 IFFT, AR, MUSIC, Modified MUSIC 기법을 적용하여 만든 ISAR 영상을 이용하여 표적 구분에 이용하고, 표적 구분에 적절한 ISAR 영상을 얻기 위한 고해상도 기법을 연구한다. 그리고 표적 구분 결과를 보여준다.

ISAR(Inverse Synthetic Aperture Radar) images represent the 2-D(two-dimensional) spatial distribution of RCS (Radar Cross Section) of an object, and they can be applied to the problem of target identification. A traditional approach to ISAR imaging is to use a 2-D IFFT(Inverse Fast Fourier Transform). However, the 2-D IFFT results in low resolution ISAR images especially when the measured frequency bandwidth and angular region are limited. In order to improve the resolution capability of the Fourier transform, various high-resolution spectral estimation approaches have been applied to obtain ISAR images, such as AR(Auto Regressive), MUSIC(Multiple Signal Classification) or Modified MUSIC algorithms. In this study, these high-resolution spectral estimators as well as 2-D IFFT approach are combined with a recently developed ISAR image classification algorithm, and their performances are carefully analyzed and compared in the framework of radar target recognition.

키워드

참고문헌

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