Multiaspect identification of submerged elastic targets via wave-based matching pursuits and hidden Markov models

Runkle, P.; Carin, Lawrence; Couchman, Luise S.; Bucaro, J. A.; Yoder, Timothy J.

doi:10.1121/1.427029

Cited by 35 publications

(26 citation statements)

References 23 publications

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“…It is well known that the acoustic signature of an object is aspect-dependent. Multiaspect HMM acoustic classification is addressed in [4] and [5] and involves training HMMs with acoustic returns taken over a sequence of different aspects. Addressing these two concerns for the case of acoustic impulse response classification is a topic of future work.…”

Section: Discussionmentioning

confidence: 99%

“…This approach has been successfully used in other underwater acoustic signal classification tasks in discriminating tonal signals from chirp and continuous-wave pulses [3]. Additionally, rather than use a standard time-frequency decomposition of the acoustic return, others have used different basis functions matched to predicted scattering wave physics as feature inputs to HMM classifiers [4], [5].…”

Section: Introductionmentioning

confidence: 99%

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Classification of Underwater Objects Via Impulse Excitation

2006

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Classification of Underwater Objects Via Impulse Excitation

2006

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“…That is (4) where and are orthogonal matrices, i.e., , , and is a diagonal singular value matrix, with and . Then, the transformation (5) resolves into their canonical coordinates , with the composite covariance matrix (6) We refer to the elements of and as the canonical coordinates of and , respectively.…”

Section: Review Of Canonical Correlation Analysismentioning

confidence: 99%

“…A detailed review of these methods is provided in [1]. However, in all these methods, multiaspect classification is performed using different classification fusion methods, namely, decision-level fusion [3] or feature-level fusion [1], [2], [4], [5]. In decisionlevel fusion, an intermediate decision about the presence and type of the object (target or nontarget) is made for every sonar return.…”

mentioning

confidence: 99%

Undersea Target Classification Using Canonical Correlation Analysis

Pezeshki

Azimi-Sadjadi

Scharf

2007

IEEE J. Oceanic Eng.

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Abstract-Canonical correlation analysis is employed as a multiaspect feature extraction method for underwater target classification. The method exploits linear dependence or coherence between two consecutive sonar returns, at different aspect angles. This is accomplished by extracting the dominant canonical correlations between the two sonar returns and using them as features for classifying mine-like objects from nonmine-like objects. The experimental results on a wideband acoustic backscattered data set, which contains sonar returns from several mine-like and nonmine-like objects in two different environmental conditions, show the promise of canonical correlation features for mine-like versus nonmine-like discrimination. The results also reveal that in a fixed bottom condition, canonical correlation features are relatively invariant to changes in aspect angle.Index Terms-Canonical correlations, linear dependence and coherence, multiaspect feature extraction, underwater target classification.

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“…Sound readily penetrates the target, and the acoustic scattering is now related to the vibrational dynamics of the object, both whole-body and internal structure. The time-frequency features 3,4 in the scattered echoes can then be used to "fingerprint" the target without the need to form an image.…”

Section: Introductionmentioning

confidence: 99%

Wide Area Detection and Identification of Underwater UXO Using Structural Acoustic Sensors

Bucaro¹,

Houston²,

Simpson³

et al. 2011

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Standard Form 298 (Rev. 8-98)Prescribed by ANSI Std. Z39.18Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information This new project is exploring the potential for developing a structural acoustics (SA) based sonar methodology for wide area search and identification of underwater unexploded ordnance (UXO). This new approach may have significant advantages over more conventional acoustic approaches, which rely on the formation of high resolution images. These advantages include: diverse set of "fingerprints" leading to low false alarm rates; longer range operation leading to wide area coverage; and low frequency sediment penetration leading to buried target prosecution. A core element of the current project is a comprehensive examination of the scattering levels and features exhibited by typical UXO targets in the SA regime using NRL's state-of-the-art underwater scattering facilities, both laboratory-based and at-sea. We have recently completed the first phase of this data collection using the laboratory-based facility, and these results are reported here. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) SPONSOR / MONITOR'S ACRONYM(S) 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) SPONSOR / MONITOR'S REPORT NUMBER(S) PROJECT BACKGROUNDMany active and former military installations have ordnance ranges and training areas with adjacent water environments in which unexploded ordnance (UXO) now exists due to wartime activities, dumping, and accidents. These contaminated areas include coastal and inland waters both in the United States and abroad. SERDP goals require the development of innovative technologies able to separate UXO from false targets and to discriminate amongst individual UXO targets themselves. Over time, such geographic areas are becoming less and less remote as the adjacent lands become further developed, and the potential hazard to the public from encounters with such UXO has begun to rise. Presently there exists no sufficiently effective capability to survey such underwater areas and map UXO locations.This new project (SERDP Project MM-1513) is exploring the potential for developing a structural acoustics (SA) based sonar methodology for wide area search and identification of underwater unexploded ordnance (UXO). This new approach may have significant advantages over more conventional acoustic approaches which rely on the formation of high resolution images.Conventional sonar approaches which form images (see Fig. 1 in Project Accomplishments Section) must operate at relatively high frequencies since the image resolution is dire...

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Multiaspect identification of submerged elastic targets via wave-based matching pursuits and hidden Markov models

Cited by 35 publications

References 23 publications

Classification of Underwater Objects Via Impulse Excitation

Classification of Underwater Objects Via Impulse Excitation

Undersea Target Classification Using Canonical Correlation Analysis

Wide Area Detection and Identification of Underwater UXO Using Structural Acoustic Sensors

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