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

The Korean Institute of Electromagnetic Engineering and Science (한국전자파학회)
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A Study on the Target Recognition Using Bistatic Measured Radar Signals

바이스태틱 레이다 측정 신호를 이용한 표적 인식에 관한 연구

  • Lee, Sung-Jun (Department of Electronic Engineering, Hannam University) ;
  • Lee, Seung-Jae (Department of Electronic Engineering, Hannam University) ;
  • Choi, In-Sik (Department of Electronic Engineering, Hannam University)
  • 이성준 (한남대학교 전자공학과) ;
  • 이승재 (한남대학교 전자공학과) ;
  • 최인식 (한남대학교 전자공학과)
  • Received : 2012.06.18
  • Accepted : 2012.08.01
  • Published : 2012.08.31
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Abstract

This paper shows the research about radar target recognition using the measured radar signals from MSU(Michgan State University) bistatic radar system. In this research, we first did the bistatic measurements at $30^{\circ}$, $60^{\circ}$, $90^{\circ}$ using F-14, Mig-29, and F-22 scale models. Then, we extract the target feature vectors using time-frequency analysis methods such as STFT(Short Time Fourier Transform) and CWT(Continous Wavelet Transform) and perform the target classification test using MLP(Multi-layerd Perceptron) neural network. The results show that the target classification performance is too much dependent on the bistatic angles and the best performance is obtained at the $60^{\circ}$ bistatic angle.

본 연구는 미시간 주립대(Michigan State University)의 바이스태틱 레이다 시스템을 통하여 수집한 측정 데이터를 이용한 표적 구분에 관한 연구 결과이다. 본 연구에서는 먼저 F-14, Mig-29, F-22 스케일 모델에 대하여 $30^{\circ}$, $60^{\circ}$, $90^{\circ}$ 바이스태틱 각도에서의 측정을 수행하였다. 측정한 데이터로부터 시간-주파수 영역 해석법인 단시간 퓨리에 변환(Short Time Fourier Transform)과 연속 웨이브릿 변환(Continous Wavelet Transform)을 이용하여 특성 벡터를 추출하고, 신경망 구분기를 통하여 표적 구분 실험을 수행하였다. 실험 결과, 바이스태틱 각도에 따라 표적 구분 성능에 많은 변화가 있으며, 특히, $60^{\circ}$ 바이스태틱 각도에서 가장 좋은 구분 성능을 가짐을 알 수 있었다.

Keywords

References

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