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...
Main Author: | |
---|---|
Other Authors: | |
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 |
id |
ftdtic:ADA384764 |
---|---|
record_format |
openpolar |
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 |
_version_ |
1766061108457635840 |