Proud elastic target discrimination using low-frequency sonar signatures

This thesis presents a comparative analysis of various low-frequency sonar signature representations and their ability to discriminate between proud targets of varying physical parameters. The signature representations used include: synthetic aperture sonar (SAS) beamformed images, acoustic color pl...

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Bibliographic Details
Other Authors: Mallen, Brenton.
Format: Others
Language:English
Published: Florida Atlantic University
Subjects:
Online Access:http://purl.flvc.org/FAU/3342210
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spelling ndltd-fau.edu-oai-fau.digital.flvc.org-fau_38812019-07-04T03:52:17Z Proud elastic target discrimination using low-frequency sonar signatures Mallen, Brenton. Text Electronic Thesis or Dissertation Florida Atlantic University English xv, 125 p. : ill. (some col.) electronic This thesis presents a comparative analysis of various low-frequency sonar signature representations and their ability to discriminate between proud targets of varying physical parameters. The signature representations used include: synthetic aperture sonar (SAS) beamformed images, acoustic color plot images, and bispectral images. A relative Mean-Square Error (rMSE) performance metric and an effective Signal-to-Noise Ratio (SNReff) performance metric have been developed and implemented to quantify the target differentiation. The analysis is performed on a subset of the synthetic sonar stave data provided by the Naval Surface Warfare Center - Panama City Division (NSWC-PCD). The subset is limited to aluminum and stainless steel, thin-shell, spherical targets in contact with the seafloor (proud). It is determined that the SAS signature representation provides the best, least ambiguous, target differentiation with a minimum mismatch difference of 14.5802 dB. The acoustic color plot and bispectrum representations resulted in a minimum difference of 9.1139 dB and 1.8829 dB, respectively by Brenton Mallen. Thesis (M.S.C.S.)--Florida Atlantic University, 2012. Includes bibliography. Electronic reproduction. Boca Raton, Fla., 2012. Mode of access: World Wide Web. Pattern recognition systems Frequency response (Dynamics) Signal theory (Telecommunication) Random noise theory http://purl.flvc.org/FAU/3342210 794840080 3342210 FADT3342210 fau:3881 College of Engineering and Computer Science Department of Ocean and Mechanical Engineering http://rightsstatements.org/vocab/InC/1.0/ https://fau.digital.flvc.org/islandora/object/fau%3A3881/datastream/TN/view/Proud%20elastic%20target%20discrimination%20using%20low-frequency%20sonar%20signatures.jpg
collection NDLTD
language English
format Others
sources NDLTD
topic Pattern recognition systems
Frequency response (Dynamics)
Signal theory (Telecommunication)
Random noise theory
spellingShingle Pattern recognition systems
Frequency response (Dynamics)
Signal theory (Telecommunication)
Random noise theory
Proud elastic target discrimination using low-frequency sonar signatures
description This thesis presents a comparative analysis of various low-frequency sonar signature representations and their ability to discriminate between proud targets of varying physical parameters. The signature representations used include: synthetic aperture sonar (SAS) beamformed images, acoustic color plot images, and bispectral images. A relative Mean-Square Error (rMSE) performance metric and an effective Signal-to-Noise Ratio (SNReff) performance metric have been developed and implemented to quantify the target differentiation. The analysis is performed on a subset of the synthetic sonar stave data provided by the Naval Surface Warfare Center - Panama City Division (NSWC-PCD). The subset is limited to aluminum and stainless steel, thin-shell, spherical targets in contact with the seafloor (proud). It is determined that the SAS signature representation provides the best, least ambiguous, target differentiation with a minimum mismatch difference of 14.5802 dB. The acoustic color plot and bispectrum representations resulted in a minimum difference of 9.1139 dB and 1.8829 dB, respectively === by Brenton Mallen. === Thesis (M.S.C.S.)--Florida Atlantic University, 2012. === Includes bibliography. === Electronic reproduction. Boca Raton, Fla., 2012. Mode of access: World Wide Web.
author2 Mallen, Brenton.
author_facet Mallen, Brenton.
title Proud elastic target discrimination using low-frequency sonar signatures
title_short Proud elastic target discrimination using low-frequency sonar signatures
title_full Proud elastic target discrimination using low-frequency sonar signatures
title_fullStr Proud elastic target discrimination using low-frequency sonar signatures
title_full_unstemmed Proud elastic target discrimination using low-frequency sonar signatures
title_sort proud elastic target discrimination using low-frequency sonar signatures
publisher Florida Atlantic University
url http://purl.flvc.org/FAU/3342210
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