Effects of sea-surface conditions on passive fathometry and bottom characterization.

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 (25 m) approximately 75 km off the coast of Savannah, GA. A Navy tower about 100 m 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 5 to 21 ms and wave heights of 1-3.4 m. 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.

[1]  Richard L. Weaver,et al.  On the emergence of the Green's function in the correlations of a diffuse field: pulse-echo using thermal phonons. , 2001, Ultrasonics.

[2]  W. Kuperman,et al.  Emergence rate of the time-domain Green's function from the ambient noise cross-correlation function , 2005 .

[3]  Philippe Roux,et al.  Arrival-time structure of the time-averaged ambient noise cross-correlation function in an oceanic waveguide. , 2005, The Journal of the Acoustical Society of America.

[4]  Stewart A. L. Glegg,et al.  Imaging the ocean with ambient noise , 1992, Nature.

[5]  P. Gerstoft,et al.  Passive fathometer processing. , 2008, The Journal of the Acoustical Society of America.

[6]  J. Claerbout,et al.  Acoustic daylight imaging via spectral factorization: helioseismology and reservoir monitoring , 1999 .

[7]  D. Halpern,et al.  Wind dependence of underwater ambient noise , 1983 .

[8]  M. Siderius,et al.  Bottom profiling by correlating beam-steered noise sequences. , 2008, The Journal of the Acoustical Society of America.

[9]  R. Weaver,et al.  Ultrasonics without a source: thermal fluctuation correlations at MHz frequencies. , 2001, Physical review letters.

[10]  M. Porter,et al.  A passive fathometer technique for imaging seabed layering using ambient noise , 2006 .

[11]  W. Kuperman,et al.  Extracting coherent wave fronts from acoustic ambient noise in the ocean , 2004 .

[12]  Jon F. Claerbout,et al.  Acoustic Daylight Imaging Via Spectral Factorization: Helioseismology And Reservoir Monitoring , 1999 .

[13]  W. Kuperman,et al.  Ambient noise cross correlation in free space: theoretical approach. , 2005, The Journal of the Acoustical Society of America.

[14]  D. Simons,et al.  Geoacoustic inversion of ambient noise: a simple method. , 2002, The Journal of the Acoustical Society of America.