Sponsor
The authors gratefully acknowledge the support of the Office of Naval Research postdoctoral fellowship and the Ocean Acoustics Program (ONR-OA Code 3211).
Published In
Journal of the Acoustical Society of America Express Letters
Document Type
Article
Publication Date
12-2012
Subjects
Underwater acoustics, Sediments (Geology) -- Acoustic properties
Abstract
This letter applies trans-dimensional Bayesian geoacoustic inversion to quantify the uncertainty due to model selection when inverting bottom-loss data derived from wind-driven ambient-noise measurements. A partition model is used to represent the seabed, in which the number of layers, their thicknesses, and acoustic parameters are unknowns to be determined from the data. Exploration of the parameter space is implemented using the Metropolis–Hastings algorithm with parallel tempering, whereas jumps between parameterizations are controlled by a reversible-jump Markov chain Monte Carlo algorithm. Sediment uncertainty profiles from inversion of simulated and experimental data are presented.
DOI
10.1121/1.4771975
Persistent Identifier
http://archives.pdx.edu/ds/psu/12064
Citation Details
Quijano, J., Dosso, S., Dettmer, J., Zurk, L., & Siderius, M. (2013). Trans-dimensional geoacoustic inversion of wind-driven ambient noise. The Journal of The Acoustical Society of America, 133(1), EL47-EL53.
Description
This is the publisher's final PDF. Copyright 2012 Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. The following article appeared in J. Acoust. Soc. Am. 133, EL47 and may be found at: http://dx.doi.org/10.1121/1.4771975