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Statistical-based feature extraction and classification of active sonar data
The Journal of the Acoustical Society of America, 2022Sonar target recognition is difficult due to the potential nonlinear overlap within an acoustic color response due to various backscatter and clutter within the ocean. This talk presents initial results from using a statistical model of feature vectors in conjunction with machine learning classifiers.
Bernice Kubicek +2 more
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Active sonar target classification using a physics-cognizant feature representation
The Journal of the Acoustical Society of America, 2021Active sonar target classification is challenging due to the non-linear overlap of changing oceanic and target parameters, creating entangled acoustic color spectra that should be disentangled prior to classification. A physics-cognizant feature extraction algorithm, used before interfacing with three machine learning techniques for active sonar target
Bernice Kubicek +2 more
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Aural classification of impulsive-source active sonar echoes
The Journal of the Acoustical Society of America, 2006The goal of this effort is to develop automatic target classification technology for active sonar systems by exploiting knowledge of signal processing methods and human auditory processing. Using impulsive-source active sonar data, formal listening experiments were conducted to determine if and how human subjects can discriminate between sonar target ...
James Pitton +6 more
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Optimum classification with active sonar: new theoretical results
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, 1991Active underwater acoustic classification is a central sonar signal processing problem. The main thrust of this work is a critical evaluation of several key issues impacting on optimum processor implementation. To this end, the authors have developed systematic methods for evaluating the performance of the overall system.
J.G. Kelly +3 more
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Contrast models and classification of active sonar signals.
The Journal of the Acoustical Society of America, 2008New features and algorithms are derived from human perception to improve the automation of active sonar signal classification. Data from human subject research on the perceived similarity of sound pairs can be assembled in the form of a dissimilarity matrix. A dissimilarity matrix can be analyzed in many ways, two of which are multidimensional scaling (
Charles F. Gaumond +2 more
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Neural networks for active sonar classification
Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol.II. Conference B: Pattern Recognition Methodology and Systems, 2003Active sonar classification has been a challenging pattern recognition problem for many years mainly due to the complexity of ocean environment. Improvement of sensors and data acquisition can be very costly and can only provide limited improvement in classification.
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Pseudo-hybrid PDF estimators for active sonar classification
The Journal of the Acoustical Society of America, 2003A class of multivariate PDF estimators for use in feature-based target classification in active sonar is presented. The goal is to develop a method that (1) preserves feature identity, (2) captures complex data structures and tails using non-parametric estimates, (3) utilizes parametric models for higher-order inter-feature dependencies, and (4 ...
James M. Gelb +2 more
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Perception-based automatic classification of impulsive-source active sonar echoes
The Journal of the Acoustical Society of America, 2007Impulsive-source active sonar systems are often plagued by false alarm echoes resulting from the presence of naturally occurring clutter objects in the environment. Sonar performance could be improved by a technique for discriminating between echoes from true targets and echoes from clutter. Motivated by anecdotal evidence that target echoes sound very
Victor W, Young, Paul C, Hines
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Automatic Object Classification with Active Sonar using Unsupervised Anomaly Detection
2020 28th European Signal Processing Conference (EUSIPCO), 2021This work describes an unsupervised anomaly detection method for automatic contacts classification of an active sonar system. The proposed method refers to littoral, shallow water environments where there is a significant amount of clutter contacts from the seafloor and coastal reverberation.
Pietro Stinco +3 more
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Classification of active sonar detections with class specific method
The Journal of the Acoustical Society of America, 2007The use of the Class Specific Method (CSM) [P. M. Baggenstoss, Trans. Sig. Proc. 47, 3428–3432 (1999)] is demonstrated with numerically simulated data. The two models of a cylindrical shell and a fish school are shown to generate sufficient statistics with appropriate assumptions. The common reference signal for the CSM is Gaussian white noise.
Charles F. Gaumond, Ralph N. Baer
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