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Jun 2004

Volume 115, Issue 6, pp. 2677-3253

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Matrix filter design for passive sonar interference suppression

Richard J. Vaccaro, Amit Chhetri, and Brian F. Harrison

J. Acoust. Soc. Am. Volume 115, Issue 6, pp. 3010-3020 (2004); (11 pages) | Cited 2 times

Online Publication Date: 03 Jun 2004

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The performance of passive acoustic signal-processing techniques can become severely degraded when the acoustic source of interest is obscured by strong interference. The application of matrix filters to suppress interference while passing a signal of interest with minimal distortion is presented. An algorithm for single-frequency matrix filter design is developed by converting a constrained convex optimization problem into a sequence of unconstrained problems. The approach is extended to broadband data by incoherently combining the responses of matrix filters designed at frequencies across a band of interest. The responses of single-frequency and multifrequency matrix filters are shown. Examples are given which demonstrate the effectiveness of matrix filtering applied to matched-field localization of a weak source in the presence of a strong interferer and noise. These examples show the matrix filter effectively suppressing the interference, thereby enabling the localization of the weak source. Standard matched-field processing, without matrix filtering, is not effective in localizing the weak source. © 2004 Acoustical Society of America.
Show PACS
43.60.Gk Space-time signal processing, other than matched field processing
43.30.Wi Passive sonar systems and algorithms, matched field processing in underwater acoustics

High-frequency (8–16 kHz) model-based source localization

Paul Hursky, Michael B. Porter, Martin Siderius, and Vincent K. McDonald

J. Acoust. Soc. Am. Volume 115, Issue 6, pp. 3021-3032 (2004); (12 pages) | Cited 2 times

Online Publication Date: 03 Jun 2004

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Matched-field or model-based processing has now been widely demonstrated for improving source localization and detection in ocean waveguides. Most of the processing approaches become increasingly sensitive to fluctuations or uncertainties as the frequency increases. As a result, there has been very limited work above 1 kHz and there is a perception that above several kilohertz the technique cannot be applied. We have conducted acoustic communications experiments in a variety of shallow water sites around coastal areas of the United States. These experiments show that a clear multipath structure is readily observed even in the 8–16 kHz band. Furthermore, it is shown that model-based processing can then be exploited to localize sources at these high frequencies out to ranges of several kilometers. © 2004 Acoustical Society of America.
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43.60.Kx Matched field processing
43.30.Wi Passive sonar systems and algorithms, matched field processing in underwater acoustics
43.60.Uv Model-based signal processing
43.30.Re Signal coherence or fluctuation due to sound propagation/scattering in the ocean

An efficient robust sound classification algorithm for hearing aids

Peter Nordqvist and Arne Leijon

J. Acoust. Soc. Am. Volume 115, Issue 6, pp. 3033-3041 (2004); (9 pages) | Cited 4 times

Online Publication Date: 03 Jun 2004

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An efficient robust sound classification algorithm based on hidden Markov models is presented. The system would enable a hearing aid to automatically change its behavior for differing listening environments according to the user’s preferences. This work attempts to distinguish between three listening environment categories: speech in traffic noise, speech in babble, and clean speech, regardless of the signal-to-noise ratio. The classifier uses only the modulation characteristics of the signal. The classifier ignores the absolute sound pressure level and the absolute spectrum shape, resulting in an algorithm that is robust against irrelevant acoustic variations. The measured classification hit rate was 96.7%–99.5% when the classifier was tested with sounds representing one of the three environment categories included in the classifier. False-alarm rates were 0.2%–1.7% in these tests. The algorithm is robust and efficient and consumes a small amount of instructions and memory. It is fully possible to implement the classifier in a DSP-based hearing instrument. © 2004 Acoustical Society of America.
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43.60.Lq Acoustic imaging, displays, pattern recognition, feature extraction
43.66.Ts Auditory prostheses, hearing aids

Time-reversal imaging with multiple signal classification considering multiple scattering between the targets

Fred K. Gruber, Edwin A. Marengo, and Anthony J. Devaney

J. Acoust. Soc. Am. Volume 115, Issue 6, pp. 3042-3047 (2004); (6 pages) | Cited 22 times

Online Publication Date: 03 Jun 2004

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The time-reversal imaging with multiple signal classification method for the location of point targets developed within the framework of the Born approximation in Lehman and Devaney [“Transmission mode time-reversal super-resolution imaging,” J. Acoust. Soc. Am. 113, 2742–2753 (2003)] is generalized to incorporate multiple scattering between the targets. It is shown how the same method can be used in the location of point targets even if there is multiple scattering between them. On the other hand, both the conventional images and the calculated values of the target scattering amplitudes are scattering model-dependent. © 2004 Acoustical Society of America.
Show PACS
43.60.Pt Signal processing techniques for acoustic inverse problems
43.35.Zc Use of ultrasonics in nondestructive testing, industrial processes, and industrial products

Microseismic source deconvolution: Wiener filter versus minimax, Fourier versus wavelets, and linear versus nonlinear

Jianye Ching, Albert C. To, and Steven D. Glaser

J. Acoust. Soc. Am. Volume 115, Issue 6, pp. 3048-3058 (2004); (11 pages) | Cited 1 time

Online Publication Date: 03 Jun 2004

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Deconvolution is commonly performed on microseismic signals to determine the time history of a dislocation source, usually modeled as combinations of forces or couples. This paper presents a new deconvolution method that uses a nonlinear thresholding estimator, which is based on the minimax framework and operates in the wavelet domain. Experiments were performed on a steel plate using artificially generated microseismic signals, which were recorded by high-fidelity displacement sensors at various locations. The source functions were deconvolved from the recorded signals by Wiener filters and the new method. Results were compared and show that the new method outperforms the other methods in terms of reducing noise while keeping the sharp features of the source functions. Other advantages of the nonlinear thresholding estimator include (1) its performance is close to that of a minimax estimator, (2) it is nonlinear and takes advantage of sparse representations under wavelet bases, and (3) its computation is faster than the fast Fourier transform. © 2004 Acoustical Society of America.
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43.60.Pt Signal processing techniques for acoustic inverse problems
43.40.Le Techniques for nondestructive evaluation and monitoring, acoustic emission
43.60.Bf Acoustic signal detection and classification, applications to control systems

Viscoacoustic wave form inversion of transmission data for velocity and attenuation

Toshiki Watanabe, Kurt T. Nihei, Seiji Nakagawa, and Larry R. Myer

J. Acoust. Soc. Am. Volume 115, Issue 6, pp. 3059-3067 (2004); (9 pages) | Cited 2 times

Online Publication Date: 03 Jun 2004

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This study investigates the performance of a frequency domain viscoacoustic full wave form nonlinear inversion to obtain high resolution images of velocity and attenuation. An efficient frequency domain implementation is applied that consists of performing a series of single frequency inversions sweeping from low to high frequency. A cascaded inversion was adopted in which the real part of the velocity is first imaged using the phase information, then the quality factor (Q) is imaged using the amplitude information. Tests with synthetic data indicate that our approach yielded better images than the simultaneous determination of the real and imaginary parts of the complex velocity. The method is applied to laboratory data obtained in a water tank with suspended acrylic bars. Broadband 200 kHz data are obtained for a crosshole configuration with a computer-controlled scanning system and piezofilm source and detector. The velocity image produced by the full wave form inversion is compared to a curved ray travel time tomography velocity image, and was observed to possess higher resolution and more precise locations of the acrylic bars. The Q image shows a lower resolution than the velocity image, but recovers the correct Q for acrylic. This method can be applied for geophysical applications targeted to soil, unconsolidated rocks, and marine sediments and also nondestructive evaluation and medical applications. © 2004 Acoustical Society of America.
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43.60.Rw Remote sensing methods, acoustic tomography
43.60.Pt Signal processing techniques for acoustic inverse problems
43.20.Hq Velocity and attenuation of acoustic waves

Eigenfunction analysis of stochastic backscatter for characterization of acoustic aberration in medical ultrasound imaging

Trond Varslot, Harald Krogstad, Eirik Mo, and Bjørn A. Angelsen

J. Acoust. Soc. Am. Volume 115, Issue 6, pp. 3068-3076 (2004); (9 pages) | Cited 4 times

Online Publication Date: 03 Jun 2004

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Presented here is a characterization of aberration in medical ultrasound imaging. The characterization is optimal in the sense of maximizing the expected energy in a modified beamformer output of the received acoustic backscatter. Aberration correction based on this characterization takes the form of an aberration correction filter. The situation considered is frequently found in applications when imaging organs through a body wall: aberration is introduced in a layer close to the transducer, and acoustic backscatter from a scattering region behind the body wall is measured at the transducer surface. The scattering region consists of scatterers randomly distributed with very short correlation length compared to the acoustic wavelength of the transmit pulse. The scatterer distribution is therefore assumed to be δ correlated. This paper shows how maximizing the expected energy in a modified beamformer output signal naturally leads to eigenfunctions of a Fredholm integral operator, where the associated kernel function is a spatial correlation function of the received stochastic signal. Aberration characterization and aberration correction are presented for simulated data constructed to mimic aberration introduced by the abdominal wall. The results compare well with what is obtainable using data from a simulated point source. © 2004 Acoustical Society of America.
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43.60.Tj Wave front reconstruction, acoustic time-reversal, and phase conjugation
43.60.Cg Statistical properties of signals and noise
43.20.Bi Mathematical theory of wave propagation
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