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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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 |
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English |
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Others
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Pattern recognition systems Frequency response (Dynamics) Signal theory (Telecommunication) Random noise theory |
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Pattern recognition systems Frequency response (Dynamics) Signal theory (Telecommunication) Random noise theory Proud elastic target discrimination using low-frequency sonar signatures |
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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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1719219168418463744 |