Spectral Feature Classification of Oceanographic Processes Using an Autonomous Underwater Vehicle

This thesis develops and demonstrates methods of classifying ocean processes using an underwater moving platform such as an Autonomous Underwater Vehicle (AUV). The "mingled spectrum principle" is established which concisely relates observations from a moving platform to the frequency-wave...

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Main Author: Zhang, Yanwu
Other Authors: MASSACHUSETTS INST OF TECH CAMBRIDGE DEPT OF OCEAN ENGINEERING
Format: Text
Language:English
Published: 2000
Subjects:
Online Access:http://www.dtic.mil/docs/citations/ADA384764
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA384764
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spelling ftdtic:ADA384764 2023-05-15T17:06:07+02:00 Spectral Feature Classification of Oceanographic Processes Using an Autonomous Underwater Vehicle Zhang, Yanwu MASSACHUSETTS INST OF TECH CAMBRIDGE DEPT OF OCEAN ENGINEERING 2000-06 text/html http://www.dtic.mil/docs/citations/ADA384764 http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA384764 en eng http://www.dtic.mil/docs/citations/ADA384764 APPROVED FOR PUBLIC RELEASE DTIC AND NTIS Physical and Dynamic Oceanography Numerical Mathematics *UNDERWATER VEHICLES *POWER SPECTRA *OCEAN MODELS *INTERNAL WAVES OCEAN WAVES THESES CONVECTION OCEANOGRAPHIC DATA DOPPLER EFFECT OCEANOGRAPHIC EQUIPMENT LABRADOR SEA FEATURE EXTRACTION AUV(AUTONOMOUS UNDERWATER VEHICLES) MINGLED SPECTRUM OCEAN CONVECTION PSD(POWER SPECTRAL DENSITY) Text 2000 ftdtic 2016-02-20T06:37:57Z This thesis develops and demonstrates methods of classifying ocean processes using an underwater moving platform such as an Autonomous Underwater Vehicle (AUV). The "mingled spectrum principle" is established which concisely relates observations from a moving platform to the frequency-wavenumber spectrum of the ocean process. For classifying different processes, an AUV is not only able to jointly utilize the time-space information, but also at a tunable proportion by adjusting its cruise speed. Based on the mingled spectrum principle, a parametric tool for designing an AUV-based spectral classifier is developed. As a case study, AUV-based classification is applied to distinguish ocean convection from internal waves. To allow for mismatch between modeled templates and real measurements, the AUV-based classifier is designed to be robust to parameter uncertainties. By simulation tests on the classifier, it is demonstrated that at a higher AUV speed, convection's distinct spatial feature is highlighted to the advantage of classification. Experimental data are used to test the AUV-based classifier. An AUV-borne flow measurement system is designed and built using, an Acoustic Doppler Velocimeter (ADV). In February 1998, the AUV acquired field data of flow velocity in the Labrador Sea Convection Experiment. The classification test result detects convection's occurrence. The thesis work provides an important foundation for future work in autonomous detection and sampling of oceanographic processes. Joint program in Oceanography/Applied Ocean Science and Engineering, Massachusetts Institute of Technology and Woods Hole Oceanographic Institution. Text Labrador Sea Defense Technical Information Center: DTIC Technical Reports database
institution Open Polar
collection Defense Technical Information Center: DTIC Technical Reports database
op_collection_id ftdtic
language English
topic Physical and Dynamic Oceanography
Numerical Mathematics
*UNDERWATER VEHICLES
*POWER SPECTRA
*OCEAN MODELS
*INTERNAL WAVES
OCEAN WAVES
THESES
CONVECTION
OCEANOGRAPHIC DATA
DOPPLER EFFECT
OCEANOGRAPHIC EQUIPMENT
LABRADOR SEA
FEATURE EXTRACTION
AUV(AUTONOMOUS UNDERWATER VEHICLES)
MINGLED SPECTRUM
OCEAN CONVECTION
PSD(POWER SPECTRAL DENSITY)
spellingShingle Physical and Dynamic Oceanography
Numerical Mathematics
*UNDERWATER VEHICLES
*POWER SPECTRA
*OCEAN MODELS
*INTERNAL WAVES
OCEAN WAVES
THESES
CONVECTION
OCEANOGRAPHIC DATA
DOPPLER EFFECT
OCEANOGRAPHIC EQUIPMENT
LABRADOR SEA
FEATURE EXTRACTION
AUV(AUTONOMOUS UNDERWATER VEHICLES)
MINGLED SPECTRUM
OCEAN CONVECTION
PSD(POWER SPECTRAL DENSITY)
Zhang, Yanwu
Spectral Feature Classification of Oceanographic Processes Using an Autonomous Underwater Vehicle
topic_facet Physical and Dynamic Oceanography
Numerical Mathematics
*UNDERWATER VEHICLES
*POWER SPECTRA
*OCEAN MODELS
*INTERNAL WAVES
OCEAN WAVES
THESES
CONVECTION
OCEANOGRAPHIC DATA
DOPPLER EFFECT
OCEANOGRAPHIC EQUIPMENT
LABRADOR SEA
FEATURE EXTRACTION
AUV(AUTONOMOUS UNDERWATER VEHICLES)
MINGLED SPECTRUM
OCEAN CONVECTION
PSD(POWER SPECTRAL DENSITY)
description This thesis develops and demonstrates methods of classifying ocean processes using an underwater moving platform such as an Autonomous Underwater Vehicle (AUV). The "mingled spectrum principle" is established which concisely relates observations from a moving platform to the frequency-wavenumber spectrum of the ocean process. For classifying different processes, an AUV is not only able to jointly utilize the time-space information, but also at a tunable proportion by adjusting its cruise speed. Based on the mingled spectrum principle, a parametric tool for designing an AUV-based spectral classifier is developed. As a case study, AUV-based classification is applied to distinguish ocean convection from internal waves. To allow for mismatch between modeled templates and real measurements, the AUV-based classifier is designed to be robust to parameter uncertainties. By simulation tests on the classifier, it is demonstrated that at a higher AUV speed, convection's distinct spatial feature is highlighted to the advantage of classification. Experimental data are used to test the AUV-based classifier. An AUV-borne flow measurement system is designed and built using, an Acoustic Doppler Velocimeter (ADV). In February 1998, the AUV acquired field data of flow velocity in the Labrador Sea Convection Experiment. The classification test result detects convection's occurrence. The thesis work provides an important foundation for future work in autonomous detection and sampling of oceanographic processes. Joint program in Oceanography/Applied Ocean Science and Engineering, Massachusetts Institute of Technology and Woods Hole Oceanographic Institution.
author2 MASSACHUSETTS INST OF TECH CAMBRIDGE DEPT OF OCEAN ENGINEERING
format Text
author Zhang, Yanwu
author_facet Zhang, Yanwu
author_sort Zhang, Yanwu
title Spectral Feature Classification of Oceanographic Processes Using an Autonomous Underwater Vehicle
title_short Spectral Feature Classification of Oceanographic Processes Using an Autonomous Underwater Vehicle
title_full Spectral Feature Classification of Oceanographic Processes Using an Autonomous Underwater Vehicle
title_fullStr Spectral Feature Classification of Oceanographic Processes Using an Autonomous Underwater Vehicle
title_full_unstemmed Spectral Feature Classification of Oceanographic Processes Using an Autonomous Underwater Vehicle
title_sort spectral feature classification of oceanographic processes using an autonomous underwater vehicle
publishDate 2000
url http://www.dtic.mil/docs/citations/ADA384764
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA384764
genre Labrador Sea
genre_facet Labrador Sea
op_source DTIC AND NTIS
op_relation http://www.dtic.mil/docs/citations/ADA384764
op_rights APPROVED FOR PUBLIC RELEASE
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