Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-22T04:21:01.543Z Has data issue: false hasContentIssue false
  • English
  • Français

Statistical Analysis of Sonar Performance Prediction in Littoral Environments

Published online by Cambridge University Press:  05 May 2011

C.-W. Wang ,
M.-C. Yuan ,
C.-R. Yang ,
Y.-Y. Chang  and
C.-F. Chen
C.-W. Wang*
Affiliation:
Department of Marine Leisure and Tourism, China College of Marine Technology and Commerce, Taipei, Taiwan 11174, R.O.C.
M.-C. Yuan*
Affiliation:
Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei, Taiwan 10617, R.O.C.
C.-R. Yang*
Affiliation:
Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei, Taiwan 10617, R.O.C.
Y.-Y. Chang*
Affiliation:
Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei, Taiwan 10617, R.O.C.
C.-F. Chen*
Affiliation:
Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei, Taiwan 10617, R.O.C.
*
*Associate Professor & Chairman
**Ph.D. candidate
***Master
****Ph.D. student
*****Professor
Get access

Abstract

This paper presents the Statistical Analysis of Passive Sonar Performance Prediction in Littoral Environments. Passive sonar performance and acoustic prediction mainly refer to the detection range. The inputs for estimating the sonar detection range include the Figure of Merit (FOM), Transmission Loss (TL), and Ambient Noise (NL) of the operation region. These inputs are directly related to the ocean environment; hence, the detection range is, too. A littoral environment is highly variable both in time and space. This paper proposes a methodology for analyzing the statistical properties of the detection range from measurements of ocean water column properties. It is found that the detection range of the southwestern region of Taiwan in the summer is 13.8km with 5.9km as the standard deviation and in the winter is 37.8km with 33.6km as the standard deviation.

Keywords

SonarOcean and acoustic fluctuationAcoustic predictionSonar performance.
Type
Technical Note
Information
Journal of Mechanics , Volume 22 , Issue 2 , June 2006 , pp. 155 - 160
Copyright
Copyright © The Society of Theoretical and Applied Mechanics, R.O.C. 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.Yang, C. R., “Statistical Analysis of the Predicted Detection Rang of Passive Sonar System,” Department of Engineering Science and Ocean Engineering, National Taiwan University, Master's thesis (2002).Google Scholar
2.Abbot, P. and Dyer, I., “Sonar Performance Predictions Incorporating Environmental Variability,” in Impact of Littoral Environmental Variability on Acoustic Predictions and Sonar Performance,. Pace, Nicholas G and Jensen, Finn B. eds., Kluwer Academic Publishers (2002).Google Scholar
3.Newhall, A.et al., “Preliminary Acoustic and Océanographie Observations from the ASIAEX 2001 South China Sea Experiment,” Woods Hole Océanographie Institute Technical Report WHOI-2001–12 (2001).CrossRefGoogle Scholar
4.Chen, C. F. and Lin, W. F., “Environmental Correlate of Acoustic Impulse Response and Arrivals with Solibore Propagation in ASIAEX SCS Experiment,” Proceeding of the ASIAEX Analysis Workshop, Taipei (2003).Google Scholar
5.Chiu, C. S., Ramp, R., Miller, C. W., Lynch, J. F., Duda, T. F. and Tsng, T. Y., “Acoustic Intensity Fluctuations Induced by South China Internal Tides and Solutions,” submitted to IEEE J. Ocean. Eng. (2003).Google Scholar
6.Duda, T. F., Lynch, J. F., Newhall, A. E., Lixin, W. and Chiu, C. S., “Fluctuation of 400Hz Sound Intensity in 2001 ASIAEX South China Sea Experiment,” submitted to IEEE. J. Ocean. Eng. (2003).Google Scholar
7.Fiscal Year 2003 Annual Reports, Ocean Atmosphere Space, US Office of Naval Research (CD format).Google Scholar
8.Proceedings of Impact of Littoral Environmental Variability on Acoustic Prediction and Sonar Performance-Acoustic Variability 2002, Pace, N. G. and Jensen, F. B., eds., SACLANT Undersea Research Centre, La Spezia, Italy, Kluwer Academic Publishers.Google Scholar
9.Etter, P. C., Underwater Acoustic Modeling Principles, Techniques and Applications, 2nd ed., Elsevier Applied Science, London (1996)Google Scholar
10.Urick, R. J., Principles of Underwater Sound, 3rd ed., McGraw-Hill, New York (1983).Google Scholar
11.Liu, C. H., “The Research of Acoustic Transmission Loss and Evaluation of Passive Sonar Perform,” Department of Apply Physics, National Ocean University, Master's thesis (1997).Google Scholar
12.Van Trees, H. L., Detection Estimation, and Modulation Theory: Part III Radar-Sonar Signal Processing and Gaussian Signals in Noise, Wiley, New York (1968).Google Scholar
13. National Center for Ocean Research, Historical CTD Database (1999).Google Scholar
14.Collins, M. D., “A Split-Step Pade Solution for the Parabolic Equation Method,” J. Acoust. Soc. Am., 93, pp. 1736–1742 (1993)CrossRefGoogle Scholar
15.Kuperman, W. A. and Ingenito, F., “Spatial Correlation of Surface Generated Noise in a Stratified Ocean,” J. Acoust. Soc. Am., 67(6), pp. 1988–1996 (1980).CrossRefGoogle Scholar
16.Chen, C. F., Lm, Y. T., Hsieh, L. W. and Yang, C. R., “Study of Ambient Noise in the Surrounding Waters of Taiwan,” Technical Report, UAL-NTU TR 0103.Google Scholar