Development of A Large-Aperture 160-Element Coherent Hydrophone Array System for Instantaneous Wide Area Ocean Acoustic Sensing

Schinault, Matthew E.; Seri, Sai Geetha; Radermacher, Max; Mohebbi-Kalkhoran, Hamed; Zhu, Chenyang; Makris, Nicholas C.; Ratilal, Purnima

doi:10.1109/oceans47191.2022.9977226

Cited by 6 publications

(1 citation statement)

References 27 publications

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“…Cod spawning shoals sizes quantified with OAWRS in Lofoten Norway, with spatial diameters of up to roughly 40 km, were used to help quantify conditions leading to Cod stock collapses [8]. These results have been obtained in tandem with advances in accurately predicting and modeling the acoustic scattering from marine life that makes OAWRS possible [6,7,[10][11][12][15][16][17][18][19][20] as well as with advances in equipment development for long-range, wide-area ocean acoustics sensing [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Optimal Automatic Wide-Area Discrimination of Fish Shoals from Seafloor Geology with Multi-Spectral Ocean Acoustic Waveguide Remote Sensing in the Gulf of Maine

2023

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Ocean Acoustic Waveguide Remote Sensing (OAWRS) enables fish population density distributions to be instantaneously quantified and continuously monitored over wide areas. Returns from seafloor geology can also be received as background or clutter by OAWRS when insufficient fish populations are present in any region. Given the large spatial regions that fish inhabit and roam over, it is important to develop automatic methods for determining whether fish are present at any pixel in an OAWRS image so that their population distributions, migrations and behaviour can be efficiently analyzed and monitored in large data sets. Here, a statistically optimal automated approach for distinguishing fish from seafloor geology in OAWRS imagery is demonstrated with Neyman–Pearson hypothesis testing which provides the highest true-positive classification rate for a given false-positive rate. Multispectral OAWRS images of large herring shoals during spawning migration to Georges Bank are analyzed. Automated Neyman-Pearson hypothesis testing is shown to accurately distinguish fish from seafloor geology through their differing spectral responses at any space and time pixel in OAWRS imagery. These spectral differences are most dramatic in the vicinity of swimbladder resonances of the fish probed by OAWRS. When such significantly different spectral dependencies exist between fish and geologic scattering, the approach presented provides an instantaneous, reliable and statistically optimal means of automatically distinguishing fish from seafloor geology at any spatial pixel in wide-area OAWRS images. Employing Kullback–Leibler divergence or the relative entropy in bits from Information Theory is shown to also enable automatic discrimination of fish from seafloor by their distinct statistical scattering properties across sensing frequency, but without the statistical optimal properties of the Neyman–Pearson approach.

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Section: Introductionmentioning

confidence: 99%

Optimal Automatic Wide-Area Discrimination of Fish Shoals from Seafloor Geology with Multi-Spectral Ocean Acoustic Waveguide Remote Sensing in the Gulf of Maine

2023

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Characterizing coastal cod vocalization using a towed hydrophone array

Seri

Schinault

Penna

et al. 2023

ICES Journal of Marine Science

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To better understand spawning vocalizations of Norwegian coastal cod (Gadus morhua), a prototype eight-element coherent hydrophone array was deployed in stationary vertical and towed horizontal modes to monitor cod sounds during an experiment in spring 2019. Depth distribution of cod aggregations was monitored concurrently with an ultrasonic echosounder. Cod vocalizations recorded on the hydrophone array are analysed to provide time–frequency characteristics, and source level distribution after correcting for one-way transmission losses from cod locations to the hydrophone array. The recorded cod vocalization frequencies range from ∼20 to 600 Hz with a peak power frequency of ∼60 Hz, average duration of 300 ms, and mean source level of 163.5 ± 7.9 dB re 1 μPa at 1 m. Spatial dependence of received cod vocalization rates is estimated using hydrophone array measurements as the array is towed horizontally from deeper surrounding waters to shallow water inlet areas of the experimental site. The bathymetric-dependent probability of detection regions for cod vocalizations are quantified and are found to be significantly reduced in shallow-water areas of the inlet. We show that the towable hydrophone array deployed from a moving vessel is invaluable because it can survey cod vocalization activity at multiple locations, providing continuous spatial coverage that is complementary to fixed sensor systems that provide continuous temporal coverage at a given location.

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Real-Time Detection, Bearing Estimation, and Whale Species Vocalization Classification From Passive Underwater Acoustic Array Data

Mohebbi-Kalkhoran,

Makris,

Ratilal

2024

IEEE Sensors J.

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Development of A Large-Aperture 160-Element Coherent Hydrophone Array System for Instantaneous Wide Area Ocean Acoustic Sensing

Cited by 6 publications

References 27 publications

Optimal Automatic Wide-Area Discrimination of Fish Shoals from Seafloor Geology with Multi-Spectral Ocean Acoustic Waveguide Remote Sensing in the Gulf of Maine

Optimal Automatic Wide-Area Discrimination of Fish Shoals from Seafloor Geology with Multi-Spectral Ocean Acoustic Waveguide Remote Sensing in the Gulf of Maine

Characterizing coastal cod vocalization using a towed hydrophone array

Real-Time Detection, Bearing Estimation, and Whale Species Vocalization Classification From Passive Underwater Acoustic Array Data

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