Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Active Sonar Target Recognition Using Fractional Fourier Transform

Fractional Fourier 변환을 이용한 능동소나 표적 인식

  • Seok, Jongwon (Department of Information and Communication, Changwon National University) ;
  • Kim, Taehwan (School of Electronics, Kyungpook National University) ;
  • Bae, Geon-Seong (School of Electronics, Kyungpook National University)
  • Received : 2013.07.03
  • Accepted : 2013.08.15
  • Published : 2013.11.30
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Abstract

Many studies in detection and classification of the targets in the underwater environments have been conducted for military purposes, as well as for non-military purpose. Due to the complicated characteristics of underwater acoustic signal reflecting multipath environments and spatio-temporal varying characteristics, active sonar target classification technique has been considered as a difficult technique. And it has difficulties in collecting actual underwater data. In this paper, we synthesized active target echoes based on ray tracing algorithm using target model having 3-dimensional highlight distribution. Then, Fractional Fourier transform was applied to synthesized target echoes to extract feature vector. Recognition experiment was performed using neural network classifier.

수중환경 하에서 표적을 탐지하고 식별하는 문제는 군사적인 목적은 물론 비군사적 목적으로도 많은 연구가 수행되어 왔다. 수중환경에서의 수중음향 신호가 시간 공간적으로 특성이 변화하며 천해 다중경로 환경을 반영하는 복잡한 특성을 보이는 점으로 인해 능동 표적인식 기술은 매우 어려운 기술로 여겨져 왔다. 또한 실제 데이터 수집의 어려움이 따르게 된다. 본 논문에서는 3차원 하이라이트 분포를 가지는 모델을 이용하여, 능동소나 표적신호를 음선 추적기법을 기반으로 하여 합성하였다. 합성된 표적신호를 대상으로 Fractional Fourier 변환을 적용하여 특징벡터를 추출하였고, 신경회로망 인식기를 이용하여 인식 실험을 수행하였다.

Keywords

References

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