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.
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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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