Range-dependent passive source localization using data from the Barents Sea tomography experiment

Matched-Field Processing (MFP) and Matched-Mode Processing (MMP) are two popular techniques for passively localizing an underwater acoustic emitter in range and depth. One major drawback of these techniques has been their sensitivity to uncertainty concerning the acoustic environment. Several method...

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Main Author: Pierce, David D.
Other Authors: Chiu, Ching-Sang, Therrien, Charles W., Atchley, Anthony A., Baker, Steven R., Miller, James H., Naval Postgraduate School, Oceanography, Electrical and Computer Engineering
Format: Thesis
Language:English
Published: Monterey, California. Naval Postgraduate School 1996
Subjects:
Online Access:https://hdl.handle.net/10945/8881
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record_format openpolar
spelling ftnavalpschool:oai:calhoun.nps.edu:10945/8881 2024-06-09T07:45:01+00:00 Range-dependent passive source localization using data from the Barents Sea tomography experiment Pierce, David D. Chiu, Ching-Sang Therrien, Charles W. Atchley, Anthony A. Baker, Steven R. Miller, James H. Naval Postgraduate School Oceanography Electrical and Computer Engineering 1996-06 84 p. application/pdf https://hdl.handle.net/10945/8881 en_US eng Monterey, California. Naval Postgraduate School https://hdl.handle.net/10945/8881 This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. Matched-field processing Source localization Thesis 1996 ftnavalpschool 2024-05-15T00:55:15Z Matched-Field Processing (MFP) and Matched-Mode Processing (MMP) are two popular techniques for passively localizing an underwater acoustic emitter in range and depth. One major drawback of these techniques has been their sensitivity to uncertainty concerning the acoustic environment. Several methods for addressing this phenomenon have been proposed in the literature, with varying degrees of success. Achieving high-quality location estimates remains a problem except in simple range-independent experiments or numerical simulations. In this study, we demonstrate an approach for robust, accurate emitter localization in a highly range-dependent real environment using MMP. The main factors contributing to successful localization are: 1) use of the high-resolution Multiple Signal Classification (MUSIC) algorithm, which performs well even when only a few robust modes can be obtained by mode filtering; and 2) use of an acoustic propagation model incorporating mode coupling, which is able to generate accurate replica fields in a strongly range-dependent environment. A secondary objective of the study was to demonstrate the application of higher-order statistical estimation techniques to reduce noise effects. Our results indicate that these techniques show unacceptable sensitivity to noise- and model-induced estimation errors and require further refinement before they will be useful in the underwater acoustic localization problem. Approved for public release; distribution is unlimited. Lieutenant Commander, United States Navy http://archive.org/details/rangedependentpa109458881 Thesis Barents Sea Naval Postgraduate School: Calhoun Barents Sea
institution Open Polar
collection Naval Postgraduate School: Calhoun
op_collection_id ftnavalpschool
language English
topic Matched-field processing
Source localization
spellingShingle Matched-field processing
Source localization
Pierce, David D.
Range-dependent passive source localization using data from the Barents Sea tomography experiment
topic_facet Matched-field processing
Source localization
description Matched-Field Processing (MFP) and Matched-Mode Processing (MMP) are two popular techniques for passively localizing an underwater acoustic emitter in range and depth. One major drawback of these techniques has been their sensitivity to uncertainty concerning the acoustic environment. Several methods for addressing this phenomenon have been proposed in the literature, with varying degrees of success. Achieving high-quality location estimates remains a problem except in simple range-independent experiments or numerical simulations. In this study, we demonstrate an approach for robust, accurate emitter localization in a highly range-dependent real environment using MMP. The main factors contributing to successful localization are: 1) use of the high-resolution Multiple Signal Classification (MUSIC) algorithm, which performs well even when only a few robust modes can be obtained by mode filtering; and 2) use of an acoustic propagation model incorporating mode coupling, which is able to generate accurate replica fields in a strongly range-dependent environment. A secondary objective of the study was to demonstrate the application of higher-order statistical estimation techniques to reduce noise effects. Our results indicate that these techniques show unacceptable sensitivity to noise- and model-induced estimation errors and require further refinement before they will be useful in the underwater acoustic localization problem. Approved for public release; distribution is unlimited. Lieutenant Commander, United States Navy http://archive.org/details/rangedependentpa109458881
author2 Chiu, Ching-Sang
Therrien, Charles W.
Atchley, Anthony A.
Baker, Steven R.
Miller, James H.
Naval Postgraduate School
Oceanography
Electrical and Computer Engineering
format Thesis
author Pierce, David D.
author_facet Pierce, David D.
author_sort Pierce, David D.
title Range-dependent passive source localization using data from the Barents Sea tomography experiment
title_short Range-dependent passive source localization using data from the Barents Sea tomography experiment
title_full Range-dependent passive source localization using data from the Barents Sea tomography experiment
title_fullStr Range-dependent passive source localization using data from the Barents Sea tomography experiment
title_full_unstemmed Range-dependent passive source localization using data from the Barents Sea tomography experiment
title_sort range-dependent passive source localization using data from the barents sea tomography experiment
publisher Monterey, California. Naval Postgraduate School
publishDate 1996
url https://hdl.handle.net/10945/8881
geographic Barents Sea
geographic_facet Barents Sea
genre Barents Sea
genre_facet Barents Sea
op_relation https://hdl.handle.net/10945/8881
op_rights This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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