Abstract
Global optimization schemes such as Simulated Annealing (SA) and Genetic Algorithms (GA), which rely on exhaustive searches, have been used increasingly in recent times for the inversion of underwater acoustic signals for bottom properties. Local optimization schemes such as the Levenberg-Marquardt algorithm (LM) and Gauss-Newton methods which rely on gradients, can compliment the global techniques near the global minimum. We use hybrid schemes which combine the GA with LM and Differential Evolution (DE) to invert for the geoacoustic properties of the bottom. The experimental data used for the inversions are SUS charge explosions acquired on a vertical hydrophone array during the Shelf Break Primer Experiment conducted south of New England in the Middle Atlantic Bight in August 1996. These signals were analyzed for their time-frequency behavior using wavelets. The group speed dispersion curves were obtained from the wavelet scalogram of the signals. Hybrid methods mentioned earlier are used for the inversion of compressional wave speeds in the sediment layers. An adiabatic normal mode routine was used to construct the replica fields corresponding to the parameters. Comparison of group speeds for modes 1 to 9 and for a range of frequencies 10 to 200 Hz was used to arrive at the best parameter fit. Error estimates based on the Hessian matrices and a posteriori mean and covariance are also computed. Resolution lengths were also calculated using the covariance matrix. The inverted sediment compressional speed profile compares well with in situ measurements.
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References
M.D. Collins and W.A. Kuperman. Focalization: Environmental focusing and source localization. J. Acoust. Soc. Am., 90(3): 1410–1422, 1991.
P. Gerstoft. Inversion of acoustic data using a combination of genetic algorithms and the Gauss-Newton approach. J. Acoust. Soc. Am., 97(4):2181–2190, 1995.
D.E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Boston, MA, 1989.
J.P. Hermand and P. Gerstoft. Inversion of broadband multitone acoustic data from the YELLOW SHARK summer experiments. IEEE J. Ocean. Eng., 21(4):324–346, 1996.
K. Koper and M. Wysession. Modelling the Earth’s Core and Lowermost Mantle with a Genetic Algorithm. http://levee.wustl.edu/seismology/koper/Papers/JGR96/pkp-ga.html/seismology/koper/Papers/JGR96/pkp-ga.html, 1996.
J. Lynch, G. Gawarkiewicz, C. Chiu, R. Pickart, J. Miller, K. Smith, A. Robinson, K. Brink, R. Beardsley, B. Sperry, and G. Potty. Shelfbreak PRIMER—An integrated acoustic and oceanographic field study in the Middle Atlantic Bight. R. Zhang and J. Zhou, (eds.), Shallow Water Acoust., pp. 205–212. China Ocean Press, Beijing, 1997.
J.F. Lynch, S.D. Rajan and G.V. Frisk. A comparison of broad band and narrow band modal inversions for bottom geoacoustic properties at a site near Corpus Christi, Texas. J. Acoust. Soc. Am., 89(2):648–665, 1991.
H. Pohlheim. Genetic and Evolutionary Algorithm for use with MATLAB—Version 1.83. http://www.systemtechnik.tu-ilmenau.de/~pohlheim/GA-Toolbox//~pohlheim/GA-Toolbox/, 1996.
G.R. Potty and J.H. Miller. Geoacoustic tomography: Range dependent inversions on a single slice. J. Comput. Acoust., in press.
G.R. Potty, J.H. Miller, and J.F. Lynch. Inversion of sediment geoacoustic properties at the New England Bight. J. Acoust. Soc. Am., in preperation.
G.R. Potty, J.H. Miller, J.F. Lynch, and K.B. Smith. Tomographic mapping of sediments in shallow water. J. Acoust. Soc. Am., 108(3):973–986, 2000.
M.B. Porter and E.L. Reiss. A numerical method for ocean acoustic normal modes. J. Acoust. Soc. Am., 76(1):244–252, 1984.
P. Ratilal, P. Gerstoft, J.T. Goh, and K.P. Yeo. Inversion of pressure data on a vertical array for seafloor geoacoustics properties. J. Comput. Acoust., 6(122):269–289, 1998.
B. Rapids, T. Nye, and T. Yamamoto. Pilot experiment for the acquisition of marine sediment properties via small scale tomography systems. J. Acoust. Soc. Am., 103(1):212–224, 1998.
M. Sambridge. Geophysical inversion with a neighbourhood algorithm-II. Appraising the ensemble. Geophysics. J. Int., 138:727–746, 1999.
R. Storn and A. Price. Differential Evolution—A simple and efficient adaptive scheme for global optimization over continuous spaces. International Computer Science Institute, Technical Report, TR-95–012, 1995.
K.B. Smith, J.G. Rojas, J.H. Miller, and G. Potty. Geoacoustic inversions in shallow water using direct methods and genetic algorithm techniques. J. Adv. Mar. Sci. Tech. Soc., 4(2):205–216, 1998.
A. Tarantola. Inverse Problem Theory—Methods for Data Fitting and Model Parameter Estimation. Elsevier, Amsterdam, 1987.
M.I. Taroudakis and M.G. Markaki. On the use of matched-field processing and hybrid algorithms for vertical slice tomography. J. Acoust. Soc. Am., 102(2):885–895, 1997.
A. Tolstoy, O. Diachok, and L.N. Frazer. Acoustic tomography via matched field processing. J. Acoust. Soc. Am., 89(3): 1119–1127, 1991.
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Potty, G.R., Miller, J.H. (2001). Nonlinear Optimization Techniques for Geoacoustic Tomography. In: Taroudakis, M.I., Makrakis, G.N. (eds) Inverse Problems in Underwater Acoustics. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-3520-8_4
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DOI: https://doi.org/10.1007/978-1-4757-3520-8_4
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