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Variation of probability of sonar detection by internal waves in the South Western Sea of Jeju Island

제주 서남부해역에서 내부파에 의한 소나 탐지확률 변화

  • Received : 2017.11.27
  • Accepted : 2018.01.30
  • Published : 2018.01.31

Abstract

Based on the measured data in the south western sea of Jeju Island during the SAVEX15(Shallow Water Acoustic Variability EXperiment 2015), the effect of internal waves on the PPD (Predictive Probability of Detection) of a sonar system was analyzed. The southern west sea of Jeju Island has complex flows due to internal waves and USC (Underwater Sound Channel). In this paper, sonar performance is predicted by probabilistic approach. The LFM (Linear Frequency Modulation) and MLS (Maximum Length Sequence) signals of 11 kHz - 31 kHz band of SAVEX15 data were processed to calculate the TL (Transmission Loss) and NL (Noise Level) at a distance of approximately 2.8 km from the source and the receiver. The PDF (Probability Density Function) of TL and NL is convoluted to obtain the PDF of the SE (Signal Excess) and the PPD according to the depth of the source and receiver is calculated. Analysis of the changes in the PPD over time when there are internal waves such as soliton packet and internal tide has confirmed that the PPD value is affected by different aspects.

2015년 5월 제주 서남부 해역에서 실시된 SAVEX15(Shallow Water Acoustic Variability EXperiment 2015) 데이터를 기반으로 내부파가 소나의 예상탐지확률(Predictive Probability of Detection, PPD)에 미치는 영향에 대하여 분석하였다. 제주 서남부 해역은 내부파, 수중음파채널 등으로 인하여 복잡한 해수 유동이 존재하는 해역이다. 본 논문에서는 확률적인 접근 방법을 통하여 소나의 성능을 예측하였다. SAVEX15 데이터 중 11 kHz ~ 31 kHz 대역대의 LFM(Linear Frequency Modulation), MLS(Maximum Length Sequence) 신호를 데이터 처리 하여 음원과 수신기가 약 2.8 km 떨어진 지점에서의 전달손실(Transmission Loss, TL)과 소음준위(Noise Level, NL) 값을 산출하였다. TL과 NL의 확률밀도함수(Probability Density Function, PDF)를 합성곱하여 신호이득에 대한 확률밀도 함수를 구하고 음원과 수신기의 수심에 따른 예상탐지확률을 산출하였다. 솔리톤 패킷과 내부조석 등의 내부파가 존재할 때 시간에 따른 예상탐지확률의 변화를 분석한 결과 각각 다른 양상으로 예상탐지확률 값에 영향을 주는 것을 확인하였다.

Keywords

References

  1. R. Urick, Principles of Underwater Sound (McGraw-Hill, New York, 1967), pp. 17-30.
  2. P. Abbot and I. Dyer, "Sonar performance predictions incorporating environmental variability," in Handbook of Impact of Littoral Environmental Variability on Acoustic Predictions and Sonar Performance, edited by N. Pace and F. Jensen (Springer, Dordrecht, 2002).
  3. H. C. Song, S. M. Kim, B. N. Kim, and S. H. Nam, "Shallow-water acoustic variability experiment 2015 (SAVEX15) in the northern East China Sea," J. Acoust. Soc. Am. 140, 3012 (2016).
  4. H. J. Lee, H. J. Lee, J. H. Park, and H. K. Ha, "Seasonal variability of internal tides around the korea strait: 3-D high-resolution model simulation" (in Korean), Ocean and Polar Res. 36, 1-12 (2014). https://doi.org/10.4217/OPR.2014.36.1.001
  5. C. Emerson, J. F. Lynch, P. Abbot, T. -T. Lin, T. F. Duda, G. G. Gawarkiewicz, and C. -F. Chen, "Acoustic propagation uncertainty and probabilistic prediction of sonar system performance in the southern East China Sea continental shelf and shelfbreak environments," IEEE J. Ocean Eng. 40, 1003-1017.(2015) https://doi.org/10.1109/JOE.2014.2362820
  6. I. Dyer, "Statistics of sound propagation in the ocean," J. Acoust. Soc. Am. 48, 337-345 (1970). https://doi.org/10.1121/1.1912133