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Keywords = Passive Ocean Acoustic Waveguide Remote Sensing (POAWRS)

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18 pages, 6206 KiB  
Article
The Effect of Attenuation from Fish on Passive Detection of Sound Sources in Ocean Waveguide Environments
by Daniel Duane, Chenyang Zhu, Felix Piavsky, Olav Rune Godø and Nicholas C. Makris
Remote Sens. 2021, 13(21), 4369; https://doi.org/10.3390/rs13214369 - 30 Oct 2021
Cited by 4 | Viewed by 2310
Abstract
Attenuation from fish can reduce the intensity of acoustic signals and significantly decrease detection range for long-range passive sensing of manmade vehicles, geophysical phenomena, and vocalizing marine life. The effect of attenuation from herring shoals on the Passive Ocean Acoustic Waveguide Remote Sensing [...] Read more.
Attenuation from fish can reduce the intensity of acoustic signals and significantly decrease detection range for long-range passive sensing of manmade vehicles, geophysical phenomena, and vocalizing marine life. The effect of attenuation from herring shoals on the Passive Ocean Acoustic Waveguide Remote Sensing (POAWRS) of surface vessels is investigated here, where concurrent wide-area active Ocean Acoustic Waveguide Remote Sensing (OAWRS) is used to confirm that herring shoals occluding the propagation path are responsible for measured reductions in ship radiated sound and corresponding detection losses. Reductions in the intensity of ship-radiated sound are predicted using a formulation for acoustic attenuation through inhomogeneities in an ocean waveguide that has been previously shown to be consistent with experimental measurements of attenuation from fish in active OAWRS transmissions. The predictions of the waveguide attenuation formulation are in agreement with measured reductions from attenuation, where the position, size, and population density of the fish groups are characterized using OAWRS imagery as well as in situ echosounder measurements of the specific shoals occluding the propagation path. Experimental measurements of attenuation presented here confirm previous theoretical predictions that common heuristic formulations employing free space scattering assumptions can be in significant error. Waveguide scattering and propagation theory is found to be necessary for accurate predictions. Full article
(This article belongs to the Section Ocean Remote Sensing)
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25 pages, 9302 KiB  
Article
Comparing Performances of Five Distinct Automatic Classifiers for Fin Whale Vocalizations in Beamformed Spectrograms of Coherent Hydrophone Array
by Heriberto A. Garcia, Trenton Couture, Amit Galor, Jessica M. Topple, Wei Huang, Devesh Tiwari and Purnima Ratilal
Remote Sens. 2020, 12(2), 326; https://doi.org/10.3390/rs12020326 - 19 Jan 2020
Cited by 16 | Viewed by 5646
Abstract
A large variety of sound sources in the ocean, including biological, geophysical, and man-made, can be simultaneously monitored over instantaneous continental-shelf scale regions via the passive ocean acoustic waveguide remote sensing (POAWRS) technique by employing a large-aperture densely-populated coherent hydrophone array system. Millions [...] Read more.
A large variety of sound sources in the ocean, including biological, geophysical, and man-made, can be simultaneously monitored over instantaneous continental-shelf scale regions via the passive ocean acoustic waveguide remote sensing (POAWRS) technique by employing a large-aperture densely-populated coherent hydrophone array system. Millions of acoustic signals received on the POAWRS system per day can make it challenging to identify individual sound sources. An automated classification system is necessary to enable sound sources to be recognized. Here, the objectives are to (i) gather a large training and test data set of fin whale vocalization and other acoustic signal detections; (ii) build multiple fin whale vocalization classifiers, including a logistic regression, support vector machine (SVM), decision tree, convolutional neural network (CNN), and long short-term memory (LSTM) network; (iii) evaluate and compare performance of these classifiers using multiple metrics including accuracy, precision, recall and F1-score; and (iv) integrate one of the classifiers into the existing POAWRS array and signal processing software. The findings presented here will (1) provide an automatic classifier for near real-time fin whale vocalization detection and recognition, useful in marine mammal monitoring applications; and (2) lay the foundation for building an automatic classifier applied for near real-time detection and recognition of a wide variety of biological, geophysical, and man-made sound sources typically detected by the POAWRS system in the ocean. Full article
(This article belongs to the Section Ocean Remote Sensing)
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26 pages, 6881 KiB  
Article
Detection, Localization and Classification of Multiple Mechanized Ocean Vessels over Continental-Shelf Scale Regions with Passive Ocean Acoustic Waveguide Remote Sensing
by Chenyang Zhu, Heriberto Garcia, Anna Kaplan, Matthew Schinault, Nils Olav Handegard, Olav Rune Godø, Wei Huang and Purnima Ratilal
Remote Sens. 2018, 10(11), 1699; https://doi.org/10.3390/rs10111699 - 29 Oct 2018
Cited by 25 | Viewed by 5221
Abstract
Multiple mechanized ocean vessels, including both surface ships and submerged vehicles, can be simultaneously monitored over instantaneous continental-shelf scale regions >10,000 km 2 via passive ocean acoustic waveguide remote sensing. A large-aperture densely-sampled coherent hydrophone array system is employed in the Norwegian Sea [...] Read more.
Multiple mechanized ocean vessels, including both surface ships and submerged vehicles, can be simultaneously monitored over instantaneous continental-shelf scale regions >10,000 km 2 via passive ocean acoustic waveguide remote sensing. A large-aperture densely-sampled coherent hydrophone array system is employed in the Norwegian Sea in Spring 2014 to provide directional sensing in 360 degree horizontal azimuth and to significantly enhance the signal-to-noise ratio (SNR) of ship-radiated underwater sound, which improves ship detection ranges by roughly two orders of magnitude over that of a single hydrophone. Here, 30 mechanized ocean vessels spanning ranges from nearby to over 150 km from the coherent hydrophone array, are detected, localized and classified. The vessels are comprised of 20 identified commercial ships and 10 unidentified vehicles present in 8 h/day of Passive Ocean Acoustic Waveguide Remote Sensing (POAWRS) observation for two days. The underwater sounds from each of these ocean vessels received by the coherent hydrophone array are dominated by narrowband signals that are either constant frequency tonals or have frequencies that waver or oscillate slightly in time. The estimated bearing-time trajectory of a sequence of detections obtained from coherent beamforming are employed to determine the horizontal location of each vessel using the Moving Array Triangulation (MAT) technique. For commercial ships present in the region, the estimated horizontal positions obtained from passive acoustic sensing are verified by Global Positioning System (GPS) measurements of the ship locations found in a historical Automatic Identification System (AIS) database. We provide time-frequency characterizations of the underwater sounds radiated from the commercial ships and the unidentified vessels. The time-frequency features along with the bearing-time trajectory of the detected signals are applied to simultaneously track and distinguish these vessels. Full article
(This article belongs to the Special Issue Remote Sensing of Target Detection in Marine Environment)
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27 pages, 5112 KiB  
Article
Continental Shelf-Scale Passive Acoustic Detection and Characterization of Diesel-Electric Ships Using a Coherent Hydrophone Array
by Wei Huang, Delin Wang, Heriberto Garcia, Olav Rune Godø and Purnima Ratilal
Remote Sens. 2017, 9(8), 772; https://doi.org/10.3390/rs9080772 - 28 Jul 2017
Cited by 23 | Viewed by 7842
Abstract
The passive ocean acoustic waveguide remote sensing (POAWRS) technique is employed to detect and characterize the underwater sound radiated from three scientific research and fishing vessels received at long ranges on a large-aperture densely-sampled horizontal coherent hydrophone array. The sounds radiated from the [...] Read more.
The passive ocean acoustic waveguide remote sensing (POAWRS) technique is employed to detect and characterize the underwater sound radiated from three scientific research and fishing vessels received at long ranges on a large-aperture densely-sampled horizontal coherent hydrophone array. The sounds radiated from the research vessel (RV) Delaware II in the Gulf of Maine, and the RV Johan Hjort and the fishing vessel (FV) Artus in the Norwegian Sea are found to be dominated by distinct narrowband tonals and cyclostationary signals in the 150 Hz to 2000 Hz frequency range. The source levels of these signals are estimated by correcting the received pressure levels for transmission losses modeled using a calibrated parabolic equation-based acoustic propagation model for random range-dependent ocean waveguides. The probability of the detection region for the most prominent signal radiated by each ship is estimated and shown to extend over areas spanning roughly 200 km in diameter when employing a coherent hydrophone array. The current standard procedure for quantifying ship-radiated sound source levels via one-third octave bandwidth intensity averaging smoothes over the prominent tonals radiated by a ship that can stand 10 to 30 dB above the local broadband level, which may lead to inaccurate or incorrect assessments of the impact of ship-radiated sound. Full article
(This article belongs to the Section Ocean Remote Sensing)
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22 pages, 4701 KiB  
Article
Diel and Spatial Dependence of Humpback Song and Non-Song Vocalizations in Fish Spawning Ground
by Wei Huang, Delin Wang and Purnima Ratilal
Remote Sens. 2016, 8(9), 712; https://doi.org/10.3390/rs8090712 - 30 Aug 2016
Cited by 21 | Viewed by 6822
Abstract
The vocalization behavior of humpback whales was monitored over vast areas of the Gulf of Maine using the passive ocean acoustic waveguide remote sensing technique (POAWRS) over multiple diel cycles in Fall 2006. The humpback vocalizations comprised of both song and non-song are [...] Read more.
The vocalization behavior of humpback whales was monitored over vast areas of the Gulf of Maine using the passive ocean acoustic waveguide remote sensing technique (POAWRS) over multiple diel cycles in Fall 2006. The humpback vocalizations comprised of both song and non-song are analyzed. The song vocalizations, composed of highly structured and repeatable set of phrases, are characterized by inter-pulse intervals of 3.5 ± 1.8 s. Songs were detected throughout the diel cycle, occuring roughly 40% during the day and 60% during the night. The humpback non-song vocalizations, dominated by shorter duration (≤3 s) downsweep and bow-shaped moans, as well as a small fraction of longer duration (∼5 s) cries, have significantly larger mean and more variable inter-pulse intervals of 14.2 ± 11 s. The non-song vocalizations were detected at night with negligible detections during the day, implying they probably function as nighttime communication signals. The humpback song and non-song vocalizations are separately localized using the moving array triangulation and array invariant techniques. The humpback song and non-song moan calls are both consistently localized to a dense area on northeastern Georges Bank and a less dense region extended from Franklin Basin to the Great South Channel. Humpback cries occur exclusively on northeastern Georges Bank and during nights with coincident dense Atlantic herring shoaling populations, implying the cries are feeding-related. Full article
(This article belongs to the Special Issue Underwater Acoustic Remote Sensing)
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