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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Monterey, California. Naval Postgraduate School
1996
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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 |
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Open Polar |
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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. |
_version_ |
1801373942027386880 |