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May 2012

Volume 131, Issue 5, pp. EL355-4232

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Relating waveguide invariant and bottom reflection phase-shift parameter P in a Pekeris waveguide

E. C. Shang, J. R. Wu, and Z. D. Zhao

J. Acoust. Soc. Am. Volume 131, Issue 5, pp. 3691-3697 (2012); (7 pages) | Cited 1 time

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The waveguide invariant β is affected by the shallow-water environment. The effect due to bottom sediment on β is investigated in this paper. It is found that the effect of sediment bottom can be concentrated on one parameter P—the bottom reflection phase-shift parameter. For a Pekeris waveguide, under Wentzel–Kramers–Brillouin (WKB) approximation, a very simple analytic relation is given: β ≈ 1 + P/(k0Heff), where Heff is the “effective depth,” and Heff = H + P/2k0. The value of β related to different high-speed sediments (including layered sediment) ranges from 1.0 to 1.5. Some numerical examples including the layered sediment case are conducted to verify this result. Good agreement between the results calculated by KRAKEN and by WKB with parameter P has been found. Hence, the application of parameter P provides a model-free platform to investigate the bottom effect on the waveguide invariant β in shallow-water.
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43.30.Dr Hybrid and asymptotic propagation theories, related experiments
43.30.Bp Normal mode propagation of sound in water

Range compensation for backscattering measurements in the difference-frequency nearfield of a parametric sonar

Kenneth G. Foote

J. Acoust. Soc. Am. Volume 131, Issue 5, pp. 3698-3709 (2012); (12 pages)

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Measurement of acoustic backscattering properties of targets requires removal of the range dependence of echoes. This process is called range compensation. For conventional sonars making measurements in the transducer farfield, the compensation removes effects of geometrical spreading and absorption. For parametric sonars consisting of a parametric acoustic transmitter and a conventional-sonar receiver, two additional range dependences require compensation when making measurements in the nonlinearly generated difference-frequency nearfield: an apparently increasing source level and a changing beamwidth. General expressions are derived for range compensation functions in the difference-frequency nearfield of parametric sonars. These are evaluated numerically for a parametric sonar whose difference-frequency band, effectively 1–6 kHz, is being used to observe Atlantic herring (Clupea harengus) in situ. Range compensation functions for this sonar are compared with corresponding functions for conventional sonars for the cases of single and multiple scatterers. Dependences of these range compensation functions on the parametric sonar transducer shape, size, acoustic power density, and hydrography are investigated. Parametric range compensation functions, when applied with calibration data, will enable difference-frequency echoes to be expressed in physical units of volume backscattering, and backscattering spectra, including fish-swimbladder-resonances, to be analyzed.
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43.30.Lz Underwater applications of nonlinear acoustics; explosions
43.30.Sf Acoustical detection of marine life; passive and active
43.60.Fg Acoustic array systems and processing, beam-forming
43.80.Jz Use of acoustic energy (with or without other forms) in studies of structure and function of biological systems

Improving riverbed sediment classification using backscatter and depth residual features of multi-beam echo-sounder systems

Dimitrios Eleftherakis, AliReza Amiri-Simkooei, Mirjam Snellen, and Dick G. Simons

J. Acoust. Soc. Am. Volume 131, Issue 5, pp. 3710-3725 (2012); (16 pages)

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Riverbed and seafloor sediment classification using acoustic remote sensing techniques is of high interest due to their high coverage capabilities at limited cost. This contribution presents the results of riverbed sediment classification using multi-beam echo-sounder data based on an empirical method. Two data sets are considered, both taken at the Waal River, namely Sint Andries and Nijmegen. This work is a follow-up to the work carried out by Amiri-Simkooei et al. [J. Acoust. Soc. Am. 126(4), 1724–1738 (2009)]. The empirical method bases the classification on features of the backscatter strength and depth residuals. A principal component analysis is used to identify the most appropriate and informative features. Clustering is then applied to the principal components resulting from this set of features to assign a sediment class to each measurement. The results show that the backscatter strength features discriminate between different classes based on the sediment properties, whereas the depth residual features discriminate classes based on riverbed forms such as the “fixed layer” (stone having riprap structure) and riverbed ripples. Combination of these two sets of features is highly recommended because they provide complementary information on both the composition and the structure of the riverbed.
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43.30.Pc Ocean parameter estimation by acoustical methods; remote sensing; imaging, inversion, acoustic tomography

Automated detection and localization of bowhead whale sounds in the presence of seismic airgun surveys

Aaron M. Thode, Katherine H. Kim, Susanna B. Blackwell, Charles R. Greene, Jr., Christopher S. Nations, Trent L. McDonald, and A. Michael Macrander

J. Acoust. Soc. Am. Volume 131, Issue 5, pp. 3726-3747 (2012); (22 pages)

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An automated procedure has been developed for detecting and localizing frequency-modulated bowhead whale sounds in the presence of seismic airgun surveys. The procedure was applied to four years of data, collected from over 30 directional autonomous recording packages deployed over a 280 km span of continental shelf in the Alaskan Beaufort Sea. The procedure has six sequential stages that begin by extracting 25-element feature vectors from spectrograms of potential call candidates. Two cascaded neural networks then classify some feature vectors as bowhead calls, and the procedure then matches calls between recorders to triangulate locations. To train the networks, manual analysts flagged 219 471 bowhead call examples from 2008 and 2009. Manual analyses were also used to identify 1.17 million transient signals that were not whale calls. The network output thresholds were adjusted to reject 20% of whale calls in the training data. Validation runs using 2007 and 2010 data found that the procedure missed 30%–40% of manually detected calls. Furthermore, 20%–40% of the sounds flagged as calls are not present in the manual analyses; however, these extra detections incorporate legitimate whale calls overlooked by human analysts. Both manual and automated methods produce similar spatial and temporal call distributions.
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43.30.Sf Acoustical detection of marine life; passive and active
43.60.Np Acoustic signal processing techniques for neural nets and learning systems
43.30.Wi Passive sonar systems and algorithms, matched field processing in underwater acoustics
43.80.Nd Effects of noise on animals and associated behavior, protective mechanisms

A spiral wave front beacon for underwater navigation: Transducer prototypes and testing

Benjamin R. Dzikowicz and Brian T. Hefner

J. Acoust. Soc. Am. Volume 131, Issue 5, pp. 3748-3754 (2012); (7 pages) | Cited 1 time

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Transducers for acoustic beacons which can produce outgoing signals with wave fronts whose horizontal cross sections are circular or spiral are studied experimentally. A remote hydrophone is used to determine its aspect relative to the transducers by comparing the phase of the circular signal to the phase of the spiral signal. The transducers for a “physical-spiral” beacon are made by forming a strip of 1–3 piezocomposite transducer material around either a circular or spiral backing. A “phased-spiral” beacon is made from an array of transducer elements which can be driven either in phase or staggered out of phase so as to produce signals with either a circular or spiral wave front. Measurements are made to study outgoing signals and their usefulness in determining aspect angle. Vertical beam width is also examined and phase corrections applied when the hydrophone is out of the horizontal plane of the beacon. While numerical simulations indicate that the discontinuity in the physical-spiral beacon introduces errors into the measured phase, damping observed at the ends of the piezocomposite material is a more significant source of error. This damping is also reflected in laser Doppler vibrometer measurements of the transducer’s surface velocity.
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43.30.Tg Navigational instruments using underwater sound
43.30.Yj Transducers and transducer arrays for underwater sound; transducer calibration
43.38.Hz Transducer arrays, acoustic interaction effects in arrays

Flow noise of an underwater vector sensor embedded in a flexible towed array

Vladimir I. Korenbaum and Alexander A. Tagiltsev

J. Acoust. Soc. Am. Volume 131, Issue 5, pp. 3755-3762 (2012); (8 pages)

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The objective of this work is to simulate the flow noise of a vector sensor embedded in a flexible towed array. The mathematical model developed, based on long-wavelength analysis of the inner space of a cylindrical multipole source, predicts the reduction of the flow noise of a vector sensor embedded in an underwater flexible towed array by means of intensimetric processing (cross-spectral density calculation of oscillatory velocity and sound-pressure-sensor responses). It is found experimentally that intensimetric processing results in flow noise reduction by 12–25 dB at mean levels and by 10–30 dB in fluctuations compared to a squared oscillatory velocity channel. The effect of flow noise suppression in the intensimetry channel relative to a squared sound pressure channel is observed, but only for frequencies above the threshold. These suppression values are 10–15 dB at mean noise levels and 3–6 dB in fluctuations. At towing velocities of 1.5–3 ms−1 and an accumulation time of 98.3 s, the threshold frequency in fluctuations is between 30 and 45 Hz.
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43.30.Yj Transducers and transducer arrays for underwater sound; transducer calibration
43.60.Uv Model-based signal processing
43.28.Ra Generation of sound by fluid flow, aerodynamic sound and turbulence

Erratum: “The energy ratio mapping algorithm: A tool to improve the energy-based detection of odontocete echolocation clicks” [J. Acoust. Soc. Am. 129, 1807–1812 (2011)]

Holger Klinck and David K. Mellinger

J. Acoust. Soc. Am. Volume 131, Issue 5, pp. 4203-4203 (2012); (1 page)

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Abstract Unavailable
Show PACS
43.30.Sf Acoustical detection of marine life; passive and active
43.80.Ev Acoustical measurement methods in biological systems and media
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