Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

A Bayesian framework for geoacoustic inversion of wind-driven ambient noise in shallow water

dc.contributor.authorQuijano, Jorge E.
dc.contributor.authorDosso, S.E.
dc.contributor.authorDettmer, Jan
dc.coverage.spatialQuebec City
dc.date.accessioned2015-12-10T22:34:47Z
dc.date.createdOctober 12-14 2011
dc.date.issued2012
dc.date.updated2016-02-24T10:29:40Z
dc.description.abstractBayesian inversion is applied to estimate the joint posterior probability density (PPD) of geoacoustic parameters. The PPD is sampled by a reversible-jump Markov chain Monte Carlo (rjMCMC) algorithm, which uses an extended Metropolis-Hasting (MH) criterion that allows trans-D jumps between parameterizations, quantifying the uncertainly due to the lack of knowledge of the model parameterization. Sequential datsets are obtained by discretizing continuous-time recordings of ambient noise. Conventional beamforming was used to estimate the BL at 8 frequencies in the range 550 Hz to 1400 Hz. The BL data at 20 uniformly-spaced grazing angles from 14° to 90° is provided to the sequential Bayesian trans-D Monte Carlo algorithm for estimation of the PPD. The geoacoustic parameters and the depth of acoustic interfaces closely resemble the true profiles.
dc.identifier.urihttp://hdl.handle.net/1885/56019
dc.publisherCanadian Acoustical Association
dc.relation.ispartofseriesAcoustics Week in Canada
dc.sourceCanadian Acoustics Vol 40 - Number 3 Proceedings of the Acoustics Week in Canada 2011
dc.source.urihttp://www.caa-aca.ca/conferences/quebec2011/index_en.html Proc: http://jcaa.caa-aca.ca/index.php/jcaa/issue/view/254/showToc
dc.subjectKeywords: Ambient noise; Bayesian frameworks; Bayesian inversion; Continuous time; Conventional beamforming; Geoacoustic inversion; Geoacoustic parameters; Grazing angles; Markov chain Monte Carlo; Model parameterization; Monte carlo algorithms; Parameterizations;
dc.titleA Bayesian framework for geoacoustic inversion of wind-driven ambient noise in shallow water
dc.typeConference paper
local.bibliographicCitation.lastpage81
local.bibliographicCitation.startpage80
local.contributor.affiliationQuijano, Jorge E., University of Victoria
local.contributor.affiliationDosso, S.E., University of Victoria
local.contributor.affiliationDettmer, Jan, College of Physical and Mathematical Sciences, ANU
local.contributor.authoruidDettmer, Jan, u5259635
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor040407 - Seismology and Seismic Exploration
local.identifier.absfor040599 - Oceanography not elsewhere classified
local.identifier.absseo970104 - Expanding Knowledge in the Earth Sciences
local.identifier.absseo810108 - Navy
local.identifier.absseo969902 - Marine Oceanic Processes (excl. climate related)
local.identifier.ariespublicationu4027924xPUB348
local.identifier.scopusID2-s2.0-84866974541
local.type.statusPublished Version

Downloads

Original bundle

Now showing 1 - 2 of 2
Loading...
Thumbnail Image
Name:
01_Quijano_A_Bayesian_framework_for_2012.pdf
Size:
201.56 KB
Format:
Adobe Portable Document Format
Loading...
Thumbnail Image
Name:
02_Quijano_A_Bayesian_framework_for_2012.pdf
Size:
103.79 KB
Format:
Adobe Portable Document Format