scholarly journals Matched field source detection and localization in high noise environments: A novel reduced-rank signal processing approach

1993 ◽  
Author(s):  
H.B. Riley ◽  
J.A. Tague
Keyword(s):  
Signal Processing ◽  
Source Detection ◽  
Field Source ◽  
High Noise ◽  
Reduced Rank ◽  
Processing Approach ◽  
Detection And Localization

COMPARISON OF LINEAR AND ORTHOGONAL BEAMFORMER PERFORMANCE FOR THE 1993 MATCHED FIELD PROCESSING BENCHMARKS

1994 ◽  
Vol 02 (03) ◽  
pp. 187-197 ◽  
Author(s):  
JOHN M. OZARD ◽  
PETER BROUWER ◽  
TIM SCHEUER
Keyword(s):  
Signal Processing ◽  
Parabolic Equation ◽  
Acoustic Signal ◽  
Processing Parameters ◽  
Minimum Variance ◽  
Source Detection ◽  
Source Position ◽  
Matched Field Processing ◽  
Detection And Localization ◽  
Gradient Models

Results are presented for the Matched Field Processing (MFP) analysis of synthetic benchmark cases, performed by a comprehensive Acoustic Signal Processing (ASP) code used in a turnkey manner. The performance of the Generalized Bartlett Beamformer (GBB), Minimum Variance (MV), and Modified Reduced Minimum Variance (MRMV) processors incorporated in the ASP code were evaluated. Matches for replicas generated using normal mode and Parabolic Equation (PE) models produced virtually identical results. However, the choice of layered versus gradient models was shown to be a cause of sufficient mismatch and to alter the source position by several increments in range and depth if sufficiently fine layering was not employed. GBB and MRMV exhibit similar levels of robustness to mismatch, while MV showed its well-known sensitivity to mismatch. Our turnkey approach indicated that MFP techniques are relatively robust with respect to source detection and localization even when suboptimal modeling and processing parameters are used.

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