힐버트-후앙 변환을 이용한 수중소음원의 식별

Identification of Underwater Ambient Noise Sources Using Hilbert-Huang Transfer

  • 황도진 (한국해양대학교 해양개발공학부) ;
  • 김재수 (한국해양대학교 해양개발공학부)
  • Hwang, Do-Jin (Division of Ocean Development Engineering, Korea Maritime University) ;
  • Kim, Jea-Soo (Division of Ocean Development Engineering, Korea Maritime University)
  • 발행 : 2008.02.28

초록

Underwater ambient noise originating from geophysical, biological, and man-made acoustic sources contains information on the source and the ocean environment. Such noise affectsthe performance of sonar equipment. In this paper, three steps are used to identify the ambient noise source, detection, feature extraction, and similarity measurement. First, we use the zero-crossing rate to detect the ambient noisesource from background noise. Then, a set of feature vectors is proposed forthe ambient noise source using the Hilbert-Huang transform and the Karhunen-Loeve transform. Finally, the Euclidean distance is used to measure the similarity between the standard feature vector and the feature vector of the unknown ambient noise source. The developed algorithm is applied to the observed ocean data, and the results are presented and discussed.

키워드

참고문헌

  1. 반지혜, 김기만, 박규식 (2004). “다중 특징 벡터를 이용한 고속 오디오 검색”, 한국음향학회 춘계학술대회논문집, 제1(s)호, pp 351-354
  2. 이인재, 이종민, 황요하, 허건수 (2004). “경험 모드 분석법을 이용한 감쇠 진동 신호의 분석”, 한국소음진동공학회 추계학술발표회논문집, pp 699-704
  3. 임태균, 배건성, 황찬식, 이형욱 (2007). “위그너-빌 분포 함수기반의 고유치 분해를 이용한 수중 천이 신호 식별”, 한국음향학회지, 제26권, 제3호, pp 123-128
  4. 조환래, 오선택, 오택환, 나정열 (2003). “고차통계 기법과 웨입렛을 이용한 수중 천이신호 탐지”, 한국음향학회지, 제22권, 제8호, pp 670-679
  5. Adam, O. (2006). “Advantages of the Hilbert Huang transform for marine mammals signals analysis”, J. Acoustic. Soc. Am., Vol 120, No 5, pp 2965-2973 https://doi.org/10.1121/1.2354003
  6. Burred, J.J. and Learch, A. (2005). “Hierachical automatic audio signal classification”, Proc of J. Audio Eng. Sec., Vol 52, pp 724-739
  7. Fukunaga, Keinosuke. (1990). Introduction to Statistical Pattern Recognition. Elsevier, 2nd ed., Academic Press, San Diego
  8. Huang, N.E., Shen Z., Long S.R., Wu M.N., Shih H.H., Zheng Q., Yen N.C., Tung C.C. and Liu H.H. (1998). “The Empirical Mode Decomposition and the Hilbert spectrum for Nonlinear and Nonstationary Time Series Analysis”, Proc. R. Soc. London, ser. A, 454, pp 903-995
  9. Knudsen V.O. (1948). Underwater Ambient Noise, pp 410-429
  10. Rabiner, L. and Juang, B.B. (1993). Fundamentals of Speech Recognition, Prentice-Hall International, Inc
  11. Ruqiang, Y. and Robert, X. G. (2005). “Transient Signal Analysis Based on Hilbert-Huang Transform”, Proc, of the IMTC, pp 1198-1202
  12. Tou, J.T. and Gonzalez, R.C. (1974). Pattern Recognition Principles, Addison-Wesley Publishing Company
  13. Wenz, M. (1962). “Acoustic Ambient Noise in the Ocean: Spectra and Sorces”, J. Acoustic. Soc. Am, No 34, pp 1936-1956
  14. Wu, W., Xueyao, L. and Rubo, Z. (2006). “Speech Detection Based on Hilbert-Huang Transform”, Proc, of the 1st IMSCCS, pp 290-293