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dc.contributor.authorNielsen, Peter L.
dc.contributor.authorMuzi, Lanfranco
dc.contributor.authorSiderius, Martin
dc.contributor.authorMiller, James H.
dc.date.accessioned2018-10-11T14:09:45Z
dc.date.available2018-10-11T14:09:45Z
dc.date.issued2013/12
dc.identifier47720
dc.identifier.govdocCMRE-FR-2013-025
dc.identifier.urihttp://hdl.handle.net/20.500.12489/676
dc.description.abstractSeabed characteristics (geoacoustic properties and scattering strength) are critical parameters for sonar performance predictions. However, this bottom information is considered very difficult and expensive to achieve in the scientific community. In this report, an efficient method for inferring the seabed properties is presented; it relies on a previous methodology using long moored or drifting hydrophone arrays. Results from the GLASS'12 and GLASS'13 sea trials demonstrate the feasibility of using the technique by deploying a hybrid autonomous underwater vehicle hosting a unique hydrophone array consisting of a five-element vertical line array and a four-element tetrahedral array. Seabed reflection and layering properties are estimated from sea surface generated ambient noise acquired during the two trials in different shallow water areas. Results from numerical modeling, data analysis and experimental measurements are presented with emphasis on comparing the seabed characterization at different locations with different bottom properties. Utilization of distant shipping was only demonstrated for the GLASS'12 trial data. The results obtained from both experiments demonstrate the potential of using autonomous underwater vehicles for seabed characterization and surface vessel tracking.
dc.formatx, 28 p. : ill. ; digital (PDF file)
dc.languageEnglish
dc.publisherCMRE
dc.subjectSeafloor characterization
dc.subjectAmbient noise
dc.subjectAcoustic scattering - Seafloor and sea surface
dc.subjectGeoacoustics
dc.subjectSonar arrays
dc.subjectPassive arrays
dc.subjectFolaga (Autonomous underwater vehicle)
dc.subjectUnderwater gliders
dc.subjectAutonomous Underwater Vehicles (AUV)
dc.titleGLider Acoustics Sensing of Sediments (GLASS): experiments and data analysis
dc.typeFormal Report (FR)


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