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Classification of marine sediments using a fuzzy logic impedance inversion model

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Date Issued:
1995
Summary:
In this dissertation, a fuzzy logic impedance inversion model is developed to classify marine sediments. Expert knowledge and fuzzy decision making constrain the inversion procedures to the resolving ability of the transmitted. The model is validated by comparing the estimated impedance profile with the measured impedance profile. A coherent surface scattering and incoherent volume scattering model are incorporated into a single geoacoustic scattering model that is applied to acoustic subbottom measurements. The reflected signal is modeled as the convolution of the transmitted processed wavelet and the impulse response of the sea bottom. The impedance of the acoustic return is inverted at the layer interfaces and the volume scattering strength is measured between layer interfaces. The model is applied to acoustic subbottom measurements obtained by an X-STAR subbottom profiler sonar system. The inversion techniques are developed for a 2-10 kHz 20 msec swept FM pulse. A fuzzy logic layer tracking procedure identifies the coherent surface scattering layer interfaces in a subbottom profile image. The peak amplitudes and locations are used as fuzzy inputs in the layer tracking rule base. The rule base determines which peak is assigned to the layer when two peaks compete for assignment or which layer is assigned to the peak when two layers compete for assignment. The fuzzy event detection algorithm estimates the impulse response of the acoustic return by complex least squares fitting parts of the transmitted wavelet with sections of the acoustic return. Reflectors are iteratively identified and removed from the return and the residual return is reprocessed. The detection procedure is constrained by the resolving ability of the matching signals and the peak envelope shape of the acoustic return. A genetic algorithm allows up to five low error reflector estimates to be processed until converging on the correct estimated impulse response (the tree branch whose summed error is minimized). The impedance is correlated with sediment bulk density by empirical relation. Experimental results validate that the fuzzy logic impedance inversion model reliably estimates the impedance of the sea bottom. The estimated impedance profiles of fifty acoustic returns are averaged and compared with measured impedance values.
Title: Classification of marine sediments using a fuzzy logic impedance inversion model.
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Name(s): DeBruin, Darryl L.
Florida Atlantic University, Degree grantor
LeBlanc, Lester R., Thesis advisor
College of Engineering and Computer Science
Department of Ocean and Mechanical Engineering
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 1995
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 150 p.
Language(s): English
Summary: In this dissertation, a fuzzy logic impedance inversion model is developed to classify marine sediments. Expert knowledge and fuzzy decision making constrain the inversion procedures to the resolving ability of the transmitted. The model is validated by comparing the estimated impedance profile with the measured impedance profile. A coherent surface scattering and incoherent volume scattering model are incorporated into a single geoacoustic scattering model that is applied to acoustic subbottom measurements. The reflected signal is modeled as the convolution of the transmitted processed wavelet and the impulse response of the sea bottom. The impedance of the acoustic return is inverted at the layer interfaces and the volume scattering strength is measured between layer interfaces. The model is applied to acoustic subbottom measurements obtained by an X-STAR subbottom profiler sonar system. The inversion techniques are developed for a 2-10 kHz 20 msec swept FM pulse. A fuzzy logic layer tracking procedure identifies the coherent surface scattering layer interfaces in a subbottom profile image. The peak amplitudes and locations are used as fuzzy inputs in the layer tracking rule base. The rule base determines which peak is assigned to the layer when two peaks compete for assignment or which layer is assigned to the peak when two layers compete for assignment. The fuzzy event detection algorithm estimates the impulse response of the acoustic return by complex least squares fitting parts of the transmitted wavelet with sections of the acoustic return. Reflectors are iteratively identified and removed from the return and the residual return is reprocessed. The detection procedure is constrained by the resolving ability of the matching signals and the peak envelope shape of the acoustic return. A genetic algorithm allows up to five low error reflector estimates to be processed until converging on the correct estimated impulse response (the tree branch whose summed error is minimized). The impedance is correlated with sediment bulk density by empirical relation. Experimental results validate that the fuzzy logic impedance inversion model reliably estimates the impedance of the sea bottom. The estimated impedance profiles of fifty acoustic returns are averaged and compared with measured impedance values.
Identifier: 12415 (digitool), FADT12415 (IID), fau:12555 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (Ph.D.)--Florida Atlantic University, 1995.
Subject(s): Fuzzy logic
Marine sediments
Acoustic impedance
Marine sediments--Acoustic properties
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/12415
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.