Journal of IKEEE (전기전자학회논문지)

Institute of Korean Electrical and Electronics Engineers (한국전기전자학회)
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Classification of Doppler Audio Signals for Moving Target Using Hidden Markov Model in Pulse Doppler Radar

펄스 도플러 레이더에서 HMM을 이용한 이동표적의 도플러 오디오 신호 식별

  • Received : 2018.08.28
  • Accepted : 2018.09.18
  • Published : 2018.09.30
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Abstract

Classification of moving targets in Pulse Doppler Radar(PDR) for surveillance and reconnaissance purposes is generally carried out based on listening and training experience of Doppler audio signals by radar operator. In this paper, we proposed the automatic classification method to identify the class of moving target with Doppler audio signals using the Mel Frequency Cepstral Coefficients(MFCC) and the Hidden Markov Model(HMM) algorithm which are widely used in speech recognition and the classification performance was analyzed and verified by simulations.

감시 및 정찰용 펄스 도플러 레이더(Pulse Doppler Radar : PDR)에서 이동표적의 식별은 일반적으로 레이더 운용자의 도플러 오디오 신호 청취 및 훈련 경험을 바탕으로 수행된다. 본 논문에서는 음성인식 분야에서 널리 이용되는 Mel Frequency Cepstral Coefficients(MFCC) 특징 파라미터와 Hidden Markov Model(HMM) 식별 기법을 이용하여 이동 표적의 클래스를 자동 식별하는 방법을 제안하고, 시뮬레이션을 통해 식별성능을 분석하고 검증하였다.

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References

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