No Access Submitted: 06 March 2009 Accepted: 06 August 2009 Published Online: 05 November 2009
The Journal of the Acoustical Society of America 126, 2234 (2009); https://doi.org/10.1121/1.3216915
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  • Steven L. Means
  • Martin Siderius
Recently, a method has been developed that exploits the correlation properties of the ocean’s ambient noise to measure water depth (a passive fathometer) and seabed layering [M. Siderius et al., J. Acoust. Soc. Am. 120, 1315–1323 (2006)]. This processing is based on the cross-correlation between the surface noise and the echo return from the seabed. To quantitatively study the dependency between processing and environmental factors such as wind speed, measurements were made using a fixed hydrophone array while simultaneously characterizing the environment. The measurements were made in 2006 in the shallow waters (25m) approximately 75km off the coast of Savannah, GA. A Navy tower about 100m from the array was used to measure wind speed and to observe the sea-surface using a video camera. Data were collected in various environmental conditions with wind speeds ranging from 5to21ms and wave heights of 13.4m. The data are analyzed to quantify the dependency of passive fathometer results on wind speeds, wave conditions, and averaging times. One result shows that the seabed reflection is detectable even in the lowest wind conditions. Further, a technique is developed to remove the environmental dependency so that the returns estimate seabed impedance.
This work was supported by Office of Naval Research base funding at the Naval Research Laboratory.
  1. 1. M. J. Buckingham, B. V. Berkhout, and S. A. L. Glegg, “Imaging the ocean with ambient noise,” Nature (London) 356, 327–329 (1992). https://doi.org/10.1038/356327a0, Google ScholarCrossref, ISI
  2. 2. C. H. Harrison and D. G. Simons, “Geoacoustic inversion of ambient noise: A simple method,” J. Acoust. Soc. Am. 112, 1377–1389 (2002). https://doi.org/10.1121/1.1506365, Google ScholarScitation, ISI
  3. 3. M. Siderius, C. H. Harrison, and M. B. Porter, “A passive fathometer technique for imaging seabed layering using ambient noise,” J. Acoust. Soc. Am. 120, 1315–1323 (2006). https://doi.org/10.1121/1.2227371, Google ScholarScitation, ISI
  4. 4. http://www.vision.caltech.edu/bouguetj/calib_doc (Last viewed 9/11/2009). Google Scholar
  5. 5. http://www.skio.usg.edu/Skioresearch/physical/sabsoon (Last viewed 9/11/2009). Google Scholar
  6. 6. C. H. Harrison and M. Siderius, “Bottom profiling by correlating beam-steered noise sequences,” J. Acoust. Soc. Am. 123, 1282–1296 (2008). https://doi.org/10.1121/1.2835416, Google ScholarScitation, ISI
  7. 7. P. Gerstoft, W. S. Hodgkiss, M. Siderius, C.-F. Huang, and C. H. Harrison, “Passive fathometer processing,” J. Acoust. Soc. Am. 123, 1297–1305 (2008). https://doi.org/10.1121/1.2831930, Google ScholarScitation, ISI
  8. 8. J. Rickett and J. Claerbout, “Acoustic daylight imaging via spectral factorization: Helioseismology and reservoir monitoring,” The Leading Edge 18, 957–960 (1999). https://doi.org/10.1190/1.1438420, Google ScholarCrossref
  9. 9. R. L. Weaver and O. I. Lobkis, “Ultrasonics without a source: Thermal fluctuation correlations at mHz frequencies,” Phys. Rev. Lett. 87, 134301 (2001). https://doi.org/10.1103/PhysRevLett.87.134301, Google ScholarCrossref, ISI
  10. 10. O. I. Lobkis and R. L. Weaver, “On the emergence of the Green’s function in the correlations of a diffuse field,” J. Acoust. Soc. Am. 110, 3011–3017 (2001). https://doi.org/10.1121/1.1417528, Google ScholarScitation, ISI
  11. 11. P. Roux, W. A. Kuperman, and the NPAL Group, “Extracting coherent wave fronts from acoustic ambient noise in the ocean,” J. Acoust. Soc. Am. 116, 1195–2003 (2004). Google ScholarScitation, ISI
  12. 12. P. Roux, K. G. Sabra, and W. A. Kuperman, “Ambient noise cross correlation in free space: Theoretical approach,” J. Acoust. Soc. Am. 117, 79–83 (2005). https://doi.org/10.1121/1.1830673, Google ScholarScitation, ISI
  13. 13. K. G. Sabra, P. Roux, and W. A. Kuperman, “Arrival-time structure of the time-average ambient noise cross-correlation function in an oceanic waveguide,” J. Acoust. Soc. Am. 117, 164–174 (2005). https://doi.org/10.1121/1.1835507, Google ScholarScitation, ISI
  14. 14. K. G. Sabra, P. Roux, and W. A. Kuperman, “Emergence rate of the time-domain Green’s function from the ambient noise cross-correlation function,” J. Acoust. Soc. Am. 118, 3524–3530 (2005). https://doi.org/10.1121/1.2109059, Google ScholarScitation, ISI
  15. 15. M. Siderius, “Analysis of passive seabed imaging techniques (a),” J. Acoust. Soc. Am. 123, 3629 (2008). https://doi.org/10.1121/1.2934859, Google ScholarScitation
  16. 16. W. S. Burdic, Underwater Acoustic System Analysis (Prentice-Hall, Englewood Cliffs, NJ, 1984). Google Scholar
  17. 17. F. B. Jensen, W. A. Kuperman, M. B. Porter, and H. Schmidt, Computational Ocean Acoustics (American Institute of Physics, New York, 1994). Google Scholar
  18. 18. B. R. Kerman, D. L. Evans, D. R. Watts, and D. Halpern, “Wind dependence of underwater ambient noise,” Boundary-Layer Meteorol. 26, 105–113 (1983). https://doi.org/10.1007/BF00121536, Google ScholarCrossref, ISI
  19. 19. McClelland Engineers, Inc., Ocean Bottom Survey, Air Combat Training Range, Naval Air Station Field and Laboratory Report No. 0813-0932, Brown and Root Development, Inc., Houston, TX, 1984. Google Scholar
  20. 20. APL-UW High-Frequency Environmental Acoustic Models Handbook (Applied Physics Laboratory, University of Washington, Seattle, WA, 1994), APL-UW TR 9407, p. 128. Google Scholar