Automated matched-field tracking in shallow water 2000 IEEE international symposium
Matched-field tracking (MFT) is the application of matched-field processing (MFP) to a moving source. This involves either post-processing MFP outputs to detect tracks of target peaks, or generalizing the search space of the processor to include candidate source tracks. The latter approach, referred...
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description | Matched-field tracking (MFT) is the application of matched-field processing (MFP) to a moving source. This involves either post-processing MFP outputs to detect tracks of target peaks, or generalizing the search space of the processor to include candidate source tracks. The latter approach, referred to as automated MFT, is examined in this paper. By integrating matched-field correlations over candidate source tracks, the true track can be detected (as determined by the highest integrated correlation) and the target track parameters estimated. In addition, the integration process results in a gain in detectibility for the true source track. For the general case of a source moving in three-dimensions through an environment which varies in three dimensions, the technique is computationally restrictive, because of the large number search parameters. However, for a vertical line array (VLA) in a range-independent environment, and an assumption of constant-depth, constant range-rate tracks, the search space is reduced to the range and depth at the beginning (or end) of the track, and the range-rate. The integration process can then be performed by a simple shift-then-average scheme applied to range-depth ambiguity-surface time samples. For a constant-velocity source, the range-rate can generally be assumed to be constant, except for a period in which it passes through the closest-point-of-approach (CPA). For that case, a CPA estimator, which attempts to match data from a moving source with that expected for candidate CPA tracks, is implemented. For horizontal line arrays (HLAs), a hybrid planewave beamforming/matched-field processing, track-before-detect (TBD) technique, which takes advantage of the azimuthal-filtering capability of HLAs to limit the bearing search, may be used. This approach provides estimates of the full track parameters (range, depth, course, and speed) with a processing load substantially lower than that required for a fully three-dimensional MFP search. These techniques are applied to experimental tonal data collected on a VLA and HLA during the 1996 Shallow Water Evaluation Cell Experiment (SWellEX-96), which occurred in 200-m water, 6 km southwest of San Diego. |
doi_str_mv | 10.1109/OCEANS.2000.881369 |
format | Conference Proceeding |
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This involves either post-processing MFP outputs to detect tracks of target peaks, or generalizing the search space of the processor to include candidate source tracks. The latter approach, referred to as automated MFT, is examined in this paper. By integrating matched-field correlations over candidate source tracks, the true track can be detected (as determined by the highest integrated correlation) and the target track parameters estimated. In addition, the integration process results in a gain in detectibility for the true source track. For the general case of a source moving in three-dimensions through an environment which varies in three dimensions, the technique is computationally restrictive, because of the large number search parameters. However, for a vertical line array (VLA) in a range-independent environment, and an assumption of constant-depth, constant range-rate tracks, the search space is reduced to the range and depth at the beginning (or end) of the track, and the range-rate. The integration process can then be performed by a simple shift-then-average scheme applied to range-depth ambiguity-surface time samples. For a constant-velocity source, the range-rate can generally be assumed to be constant, except for a period in which it passes through the closest-point-of-approach (CPA). For that case, a CPA estimator, which attempts to match data from a moving source with that expected for candidate CPA tracks, is implemented. For horizontal line arrays (HLAs), a hybrid planewave beamforming/matched-field processing, track-before-detect (TBD) technique, which takes advantage of the azimuthal-filtering capability of HLAs to limit the bearing search, may be used. This approach provides estimates of the full track parameters (range, depth, course, and speed) with a processing load substantially lower than that required for a fully three-dimensional MFP search. These techniques are applied to experimental tonal data collected on a VLA and HLA during the 1996 Shallow Water Evaluation Cell Experiment (SWellEX-96), which occurred in 200-m water, 6 km southwest of San Diego.</description><identifier>ISBN: 9780780365513</identifier><identifier>ISBN: 0780365518</identifier><identifier>DOI: 10.1109/OCEANS.2000.881369</identifier><language>eng</language><publisher>IEEE</publisher><subject>Array signal processing ; Background noise ; Parameter estimation ; Position measurement ; Sampling methods ; Target tracking ; Water resources</subject><ispartof>OCEANS 2000 MTS/IEEE Conference and Exhibition. Conference Proceedings (Cat. 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However, for a vertical line array (VLA) in a range-independent environment, and an assumption of constant-depth, constant range-rate tracks, the search space is reduced to the range and depth at the beginning (or end) of the track, and the range-rate. The integration process can then be performed by a simple shift-then-average scheme applied to range-depth ambiguity-surface time samples. For a constant-velocity source, the range-rate can generally be assumed to be constant, except for a period in which it passes through the closest-point-of-approach (CPA). For that case, a CPA estimator, which attempts to match data from a moving source with that expected for candidate CPA tracks, is implemented. For horizontal line arrays (HLAs), a hybrid planewave beamforming/matched-field processing, track-before-detect (TBD) technique, which takes advantage of the azimuthal-filtering capability of HLAs to limit the bearing search, may be used. This approach provides estimates of the full track parameters (range, depth, course, and speed) with a processing load substantially lower than that required for a fully three-dimensional MFP search. These techniques are applied to experimental tonal data collected on a VLA and HLA during the 1996 Shallow Water Evaluation Cell Experiment (SWellEX-96), which occurred in 200-m water, 6 km southwest of San Diego.</description><subject>Array signal processing</subject><subject>Background noise</subject><subject>Parameter estimation</subject><subject>Position measurement</subject><subject>Sampling methods</subject><subject>Target tracking</subject><subject>Water resources</subject><isbn>9780780365513</isbn><isbn>0780365518</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2000</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj1tLw0AQhRdEUGr-QJ_2DyTu7CZ7eSwhaqHYh-pzme7FruZSkpTSf-9KhcMMh284zCFkCawAYOZ5Wzer913BGWOF1iCkuSOZUZolCVlVIB5INk3fiYOSQnN4JLvVeR46nL2jadqjd3mIvnV0HtH-xP6Lxp5OR2zb4UIv6W6kf_l03TRNQsn3OMehx5ZO1-40TPHcPZH7gO3ks_-9IJ8vzUf9lm-2r-t6tckjsHLOpVQWGFdamSC9c9aXJQdADJVChR5dhY6ZAyoZ0q8A3JqAOljOvIGDFguyvOVG7_3-NMYOx-v-1lz8AuGbT1w</recordid><startdate>2000</startdate><enddate>2000</enddate><creator>Baxley, P.A.</creator><creator>Brannan, R.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>2000</creationdate><title>Automated matched-field tracking in shallow water 2000 IEEE international symposium</title><author>Baxley, P.A. ; Brannan, R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i104t-667c1027879f6eddce44211aaf57a7aead5ad09ba76f821112c9fa8fc20e91b83</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Array signal processing</topic><topic>Background noise</topic><topic>Parameter estimation</topic><topic>Position measurement</topic><topic>Sampling methods</topic><topic>Target tracking</topic><topic>Water resources</topic><toplevel>online_resources</toplevel><creatorcontrib>Baxley, P.A.</creatorcontrib><creatorcontrib>Brannan, R.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Baxley, P.A.</au><au>Brannan, R.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Automated matched-field tracking in shallow water 2000 IEEE international symposium</atitle><btitle>OCEANS 2000 MTS/IEEE Conference and Exhibition. Conference Proceedings (Cat. No.00CH37158)</btitle><stitle>OCEANS</stitle><date>2000</date><risdate>2000</risdate><volume>2</volume><spage>869</spage><epage>875 vol.2</epage><pages>869-875 vol.2</pages><isbn>9780780365513</isbn><isbn>0780365518</isbn><abstract>Matched-field tracking (MFT) is the application of matched-field processing (MFP) to a moving source. This involves either post-processing MFP outputs to detect tracks of target peaks, or generalizing the search space of the processor to include candidate source tracks. The latter approach, referred to as automated MFT, is examined in this paper. By integrating matched-field correlations over candidate source tracks, the true track can be detected (as determined by the highest integrated correlation) and the target track parameters estimated. In addition, the integration process results in a gain in detectibility for the true source track. For the general case of a source moving in three-dimensions through an environment which varies in three dimensions, the technique is computationally restrictive, because of the large number search parameters. However, for a vertical line array (VLA) in a range-independent environment, and an assumption of constant-depth, constant range-rate tracks, the search space is reduced to the range and depth at the beginning (or end) of the track, and the range-rate. The integration process can then be performed by a simple shift-then-average scheme applied to range-depth ambiguity-surface time samples. For a constant-velocity source, the range-rate can generally be assumed to be constant, except for a period in which it passes through the closest-point-of-approach (CPA). For that case, a CPA estimator, which attempts to match data from a moving source with that expected for candidate CPA tracks, is implemented. For horizontal line arrays (HLAs), a hybrid planewave beamforming/matched-field processing, track-before-detect (TBD) technique, which takes advantage of the azimuthal-filtering capability of HLAs to limit the bearing search, may be used. This approach provides estimates of the full track parameters (range, depth, course, and speed) with a processing load substantially lower than that required for a fully three-dimensional MFP search. These techniques are applied to experimental tonal data collected on a VLA and HLA during the 1996 Shallow Water Evaluation Cell Experiment (SWellEX-96), which occurred in 200-m water, 6 km southwest of San Diego.</abstract><pub>IEEE</pub><doi>10.1109/OCEANS.2000.881369</doi></addata></record> |
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subjects | Array signal processing Background noise Parameter estimation Position measurement Sampling methods Target tracking Water resources |
title | Automated matched-field tracking in shallow water 2000 IEEE international symposium |
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