Matched field inversion of geoacoustic model parameters using adaptive simulated annealing

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dc.contributor.authorLindsay, Colin Edwardsen_US
dc.date.accessioned2024-08-14T21:06:03Z
dc.date.available2024-08-14T21:06:03Z
dc.date.copyright1992en_US
dc.date.issued1992
dc.degree.departmentDepartment of Physics and Astronomy
dc.degree.levelMaster of Science M.Sc.en
dc.description.abstractA 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.en
dc.format.extent87 pages
dc.identifier.urihttps://hdl.handle.net/1828/18691
dc.rightsAvailable to the World Wide Weben_US
dc.subjectUN SDG 14: Life Below Wateren
dc.titleMatched field inversion of geoacoustic model parameters using adaptive simulated annealingen_US
dc.typeThesisen_US

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