Bowhead whale localization and environmental characterization in the Chukchi Sea using nonlinear Bayesian inversion

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dc.contributor.authorWarner, Graham Andrew
dc.contributor.supervisorDosso, Stanley Edward
dc.date.accessioned2016-09-09T22:32:47Z
dc.date.available2016-09-09T22:32:47Z
dc.date.copyright2016en_US
dc.date.issued2016-09-09
dc.degree.departmentSchool of Earth and Ocean Sciencesen_US
dc.degree.levelDoctor of Philosophy Ph.D.en_US
dc.description.abstractThis thesis develops and applies nonlinear Bayesian inversion methods for localization of bowhead whales and environmental characterization, with quantitative uncertainty estimation, based on acoustic measurements from a set of asynchronous single-channel recorders in the Chukchi Sea. Warping analysis is applied to estimate modal-dispersion data from airgun sources and whale calls. Whale locations and the water-column sound-speed profile (SSP) and seabed geoacoustic properties are estimated using reversible-jump Markov-chain Monte Carlo sampling in trans-dimensional inversions that account for uncertainty in the number of SSP nodes and subbottom layers. The estimated SSP and seafloor sound speed are in excellent agreement with independent estimates, and whale localization uncertainties decrease substantially when jointly-inverting data from multiple whale calls. Bowhead whales are also localized using a fixed-dimensional inversion of time-difference-of-arrival data derived using cross-correlation for the same recorders. The nonlinear localization uncertainty estimates are found to depend strongly on the source locations and receiver geometry.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/7539
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectBayesianen_US
dc.subjectbowheaden_US
dc.subjectlocalizationen_US
dc.subjectunderwateren_US
dc.subjectacousticsen_US
dc.subjectinversionen_US
dc.subjectwhaleen_US
dc.subjectdispersionen_US
dc.titleBowhead whale localization and environmental characterization in the Chukchi Sea using nonlinear Bayesian inversionen_US
dc.typeThesisen_US

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