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Extraction of an Underwater Transient Signal Using Sound Mask-filter

사운드 마스크 필터를 이용한 수중 과도 신호 추출

  • Bok, Tae-Hoon (Department of Ocean System Engineering, Jeju National University) ;
  • Kim, Juho (Department of Ocean System Engineering, Jeju National University) ;
  • Paeng, Dong-Guk (Department of Ocean System Engineering, Jeju National University) ;
  • Lee, Chong Hyun (Department of Ocean System Engineering, Jeju National University) ;
  • Bae, Jinho (Department of Ocean System Engineering, Jeju National University) ;
  • Kim, Seongil
  • 복태훈 (제주대학교 해양시스템공학과) ;
  • 김주호 (제주대학교 해양시스템공학과) ;
  • 팽동국 (제주대학교 해양시스템공학과) ;
  • 이종현 (제주대학교 해양시스템공학과) ;
  • 배진호 (제주대학교 해양시스템공학과) ;
  • 김성일 (국방과학연구소 제6기술연구본부)
  • Received : 2012.06.15
  • Accepted : 2012.09.14
  • Published : 2012.11.30

Abstract

An underwater transient signal is distinguished from an ambient noise. Database for the underwater transient signal is required since the underwater transient signal shows various characteristics depending on acoustic features. In the paper, hence, sound mask-filter was applied to extract the transient signals which exist temporally and locally in the ocean. The standard signal was chosen and cross-correlated with the raw signal. A mask-filter for a transient signal was obtained using the threshold which was decided by the maximum likelihood method in the envelope of the cross-correlated signal. Using the sound mask-filter, the transient signal of a sea catfish {Galeichthys felis (Linnaeus)} was extracted from the underwater ambient noise. Similarly, the man-made signal was added into the noise and it was extracted by the same method. We also have demonstrated the significance of the transient signal through comparing the extracted signals depending on the standard signal. In the results, the proposed method, sound mask-filtering, could be utilized as a database construction of the transient signals in underwater noise. Particularly, this study would be useful to extract the wanted signal from arbitrary signals.

수중 과도 신호는 주변 소음과는 구별된다. 과도 신호는 음향학적 특색에 따라 특징들이 다양하기 때문에 데이터베이스화가 요구된다. 이에 본 논문에서는 해양에서 국지적이고 일시적으로 존재하는 과도 신호를 추출하기위해 사운드 마스크 필터링 방법을 활용하였다. 표준 신호를 선택하여 원 음원과의 상호상관관계를 구하였다. 상호상관신호의 포락선에서 최대우도법에 의해 결정된 역치를 사용하여 과도 신호를 위한 사운드 마스크 필터를 구하였다. 사운드 마스크 필터를 활용하여, 수중 소음원에서 바다메기의 과도 신호를 추출하였다. 유사하게, 원 음원에 인위적으로 인공 신호를 추가한 신호에서 동일한 방식으로 바다메기와 인공 신호를 과도 신호로서 추출하였다. 또한 표준신호에 따라서 다르게 추출된 과도신호의 비교를 통해 표준신호 선택의 중요함을 제시하였다. 본 논문에서 제안된 사운드 마스크 필터링 방법은 해양 주변 소음원에서 과도 신호의 데이터베이스 구축에 활용될 수 있고, 특히, 임의의 신호에서 원하는 신호를 추출하는 데에 활용 가능성이 있다.

Keywords

References

  1. X. Lurton, An introduction to underwater acoustics: principles and applications, Springer, New York, 2010.
  2. R. J. Urick, Principles of underwater sound, McGraw-Hill, New York, 1983.
  3. H. Medwin and C. S. Clay, Fundamentals of acoustical oceanography, Academic Press, Boston, 1998.
  4. G. M. Wenz, "Acoustic ambient noise in the ocean: spectra and sources," J. Acoust. Soc. Am., vol. 34, no. 12, pp. 1936-1956, 1962. https://doi.org/10.1121/1.1909155
  5. S. Vagle, W. G. Large and D. M. Farmer, "An evaluation of the WOTAN technique of inferring oceanic winds from underwater ambient sound," J. Atmos. Oceanic Technol., vol. 7, no. 4, pp. 576-595, 1990. https://doi.org/10.1175/1520-0426(1990)007<0576:AEOTWT>2.0.CO;2
  6. J. A. Nystuen and H. D. Selsor, "Weather classification using passive acoustic drifters," J. Atmos. Oceanic Technol., vol. 14, no. 3, pp. 656-666, 1997. https://doi.org/10.1175/1520-0426(1997)014<0656:WCUPAD>2.0.CO;2
  7. P. C. Etter, "Recent advances in underwater acoustic modelling and simulation," J. Sound Vibr., vol. 240, no. 2, pp. 351-383, 2001. https://doi.org/10.1006/jsvi.2000.3212
  8. J. A. Scrimger, D. J. Evans, G. A. McBean, D. M. Farmer and B. R. Kerman, "Underwater noise due to rain, hail, and snow," J. Acoust. Soc. Am., vol. 81, no. 1, pp. 79-86, 1987. https://doi.org/10.1121/1.394936
  9. S. O. McConnell, M. P. Schilt and J. G. Dworski, "Ambient noise measurements from 100 Hz to 80 kHz in an Alaskan fjord," J. Acoust. Soc. Am., vol. 91, no. 4, pp. 1990-2003, 1992. https://doi.org/10.1121/1.403683
  10. P. D. Thorne, "The measurement of acoustic noise generated by moving artificial sediments," J. Acoust. Soc. Am., vol. 78, no. 3, pp. 1013-1023, 1985. https://doi.org/10.1121/1.393018
  11. P. D. Thorne, "Seabed saltation noise," in Natural physical sources of underwater sound, edited by B. Kerman, Kluwer Academic, Dordrecht, pp. 721-744, 1993.
  12. R. J. Urick, "Noise signature of an aircraft in level flight over a hydrophone in the sea," J. Acoust. Soc. Am., vol. 52, no. 3, pp. 993-999, 1972. https://doi.org/10.1121/1.1913206
  13. M. J. Buckingham, "Acoustical remote of the sea bed using propeller noise from a light aircraft," in Sound in the sea: from ocean acoustics to acoustical oceanography, edited by H. Medwin, Cambridge University Press, Cambridge, pp. 581-597, 2005.
  14. J. Szczucka, "Acoustic studies of diving birds in the Arctic," Proc. UAM 2009, pp. 1181-1188, 2009.
  15. 한국음향학회, 음향 용어 사전, 교학사, 서울, 2003.
  16. B. Boashash and P. O'Shea, "A methodology for detection and classification of some underwater acoustic signals using time-frequency analysis techniques," IEEE Trans. Acoust. , Speech, Signal Processing, vol. 38, no. 11, pp. 1829-1841, 1990. https://doi.org/10.1109/29.103085
  17. P. M. Oliveira, V. Lobo, V. Barroso and F. Moura- Pires, "Detection and classification of underwater transients with data driven methods based on time-frequency distributions and non-parametric classifiers," OCEANS '02 MTS/IEEE vol. 1, pp. 12-16, 2002.
  18. T. S. -. Leung and P. R. White, "A fuzzy logic based underwater acoustic transient classifier," Proceedings of 1996 IEEE Digital Signal Processing Workshop, pp. 494-497, 1996.
  19. A. Kundu, G. C. Chen and C. E. Persons, "Transient sonar signal classification using hidden Markov models and neural nets," IEEE J. Ocean. Eng., vol. 19, no. 1, pp. 87-99, 1994. https://doi.org/10.1109/48.289454
  20. S. Tucker and G. J. Brown, "Classification of transient sonar sounds using perceptually motivated features," IEEE J. Ocean. Eng., vol. 30, no. 3, pp. 588-600, 2005. https://doi.org/10.1109/JOE.2005.850910
  21. K. D. Kryter, The effects of noise on man, Academic Press, 1970.
  22. C. Beaugeant, V. Turbin, P. Scalart and A. Gilloire, "New optimal filtering approaches for hands-free telecommunication terminals," Signal Process., vol. 64, no. 1, pp. 33-47, 1998. https://doi.org/10.1016/S0165-1684(97)00174-6
  23. N. Virag, "Single channel speech enhancement based on masking properties of the human auditory system," IEEE Tran. Speech Audio Processing, vol. 7, no. 2, pp. 126-137, 1999. https://doi.org/10.1109/89.748118
  24. J. G. Proakis and D. G. Manolakis, Digital signal processing: principles, algorithm, and applications, Prentice Hall, New Jersey, 1996.
  25. J. L. Melsa and D. L. Cohn, Decision and estimation theory, McGraw-Hill, New York, 1978.

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