Results 181 to 190 of about 1,393 (219)
Similarity-Based Perceptual Feature Identification for Active Sonar Signal Classification
The Journal of the Acoustical Society of America, 2008 In many acoustic signal processing applications human listeners are able to outperform automated processing techniques, particularly in the identification and classification of acoustic events. This paper develops a framework for employing perceptual information from human listening experiments to improve automatic classification of active sonar ...
Scott M. Philips, James W. Pitton
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Environmentally tolerant waveguide-invariant target depth classification for active sonar.
The Journal of the Acoustical Society of America, 2010 Shallow-water environments produce active sonar returns with many target-like returns from bottom clutter. Scatterer depth classification methods which can discriminate bottom clutter from water column targets are thus critical for controlling false alarms. In recent work, the waveguide invariant (WI) property of shallow-water channels has been used to
Ryan Goldhahn +2 more
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[1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering, 2002 Summary form only given as follows. Although there has been little progress in conventional statistical and syntactic pattern recognition, the reemerging activity in neural networks and in artificial intelligence (AI) knowledge-based systems has had great impact in sonar and other applications. This impact is noted in the context of active sonar signal
Caidong Chen
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Active sonar classification using perceptual signal features from musical acoustics
The Journal of the Acoustical Society of America, 2006 Because of the relatively low frequencies at which they operate, navy active sonars are often plagued by false-alarm returns resulting from geological structures. In the lexicon of sonar operators these false returns are referred to as geoclutter or simply clutter.
Victor W. Young +2 more
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Issues In Neural Networks For Active Sonar Classification
OCEANS 92 Proceedings@m_Mastering the Oceans Through Technology, 2005 C.H. Chen
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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 classification using Bayesian decision theory
[1990] Proceedings. The Twenty-Second Southeastern Symposium on System Theory, 2002Consideration is given to the performance analysis of optimal sonar classification. To perform active classification, a known waveform is transmitted into a medium and directed toward a region called the test volume. An array of N sensors is used to pick up the backscattered signal energy reflected from the M cells of the test volume, and the data are ...
R.N. Carpenter +3 more
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Noncontact Wideband Sonar for Human Activity Detection and Classification
IEEE Sensors Journal, 2014This paper suggests using a wideband sonar system to detect and classify human activity in indoor environment. The high bandwidth enables precise tracking of body parts, and its enhanced correlation properties can be used to dis- tinguish between human and nonhuman objects.
Gaddi Blumrosen +2 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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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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