Matched field inversion of geoacoustic model parameters using adaptive simulated annealing
Date
1992
Authors
Lindsay, Colin Edwards
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Abstract
A method has been developed for the estimation of geoacoustic model parameters by the inversion of acoustic field data using a non-linear optimization procedure based on simulated annealing. The cost function used by the algorithm is the Bartlett matched field processor which relates the measured acoustic field with replica fields calculated by the SAFARI program. Model parameters are perturbed randomly, and the algorithm searches the multidimensional parameter space of geoacoustic models to determine the parameter set corresponding to the best replica field. Convergence is driven by adaptively guiding the search to regions of the parameter space associated with above-average values of the matched field processor. The performance of the method is demonstrated for a vertical line array in a shallow water environment in which the bottom consists of homogeneous elastic solid layers. Simulated data are used to study the effects of uncertainty in the experimental geometry and noise contamination on parameter estimation. Results are presented for the inversion of data obtained in an experiment off the West Coast of Vancouver Island.
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UN SDG 14: Life Below Water