Passive Ocean Acoustic Waveguide Remote Sensing Research Articles

Humpback whale song vocalization behavior and temporo-spatial distributions in the Norwegian and Barents Sea observed with a coherent hydrophone array

The vocalization behavior of humpback whales in the Norwegian and Barents Seas is examined based on recordings of a large-aperture, densely-populated coherent hydrophone array system. The passive ocean acoustic waveguide remote sensing (POAWRS) technique is employed to provide detection, bearing-time estimation, time-frequency characterization and classification of the humpback whale vocalizations. The song vocalizations, composed of highly structured and repeatable set of phrases, were detected throughout the diel cycle between February 18 to March 8, 2014. The beamformed spectrograms of the detected humpback vocalizations are classified as song sequences based on inter-pulse intervals and time-frequency characteristics, verified by visual inspection. The song structure is compared for humpback whale vocalizations recorded at three distinct regions off the Norwegian coast, Alesund, Lofoten and Northern Finmark. Multiple bearing-time trajectories for humpback songs were simultaneously observed indicating multiple singers present at each measurement site. Humpback whale received call rates and temporo-spatial distributions are compared across the three measurement sites. Geographic mapping of humpback whale calls from their bearing-time trajectories is accomplished via the moving array triangulation technique.

Directional soundscapes in the Norwegian Seas observed with a coherent hydrophone array

Directional soundscaping is an efficient approach for examining marine ecosystems since it allows the study of living organisms, their behavior, and temporo-spatial interactions with other natural and man-made objects underwater, useful for ecosystem monitoring during offshore energy activities, maritime surveillance, and defense. A large aperture coherent hydrophone array was employed for remote sensing in the Norwegian and Barents Seas in Spring 2014. Extensive analysis have been conducted in post-processing of recorded hydrophone array data for automatic detection, bearing estimation, and classification of signals by different sound producers, such as whale calls, ship radiated noise, and fish sounds. Directional soundscaping through passive ocean acoustic waveguide remote sensing (POAWRS) provides bearing-time trajectories of signal detections that can be applied for geographical mapping. The received marine mammal sounds include vocalizations from baleen whales such as humpback, fin, and minke, and toothed whales, such as beluga, pilot, and sperm. We provide an insight to the vocalizations and behaviorial patterns of these whales in the Lofoten and Northern Finmark regions. The relative contributions of distinct sound sources, including whales, fish, and ships, to the directional soundscapes are quantified. We also examine their temporo-spatial dependences via geographic mapping of acoustic signals from distinct sound producers.

Acoustic diversity, bearing estimation, and localization of sound sources in shallow water and deep ocean off the U.S. Northeast coast using a coherent hydrophone array

An in-house developed 160-element large-aperture hydrophone array from Northeastern University was utilized for ocean monitoring in both the shallow waters of the Great South Channel (GSC) and the deep-water area off the continental slope south of Rhode Island in September 2021. Utilizing passive ocean acoustic waveguide remote sensing (POAWRS) technology, the system enabled real-time, broad-area surveillance of the oceanic environment. A novel multistage clustering was introduced for annotating the vast volume of underwater acoustic data, drawing inspiration from the human cognitive process of categorizing sounds. Initially, sounds are separated into broad groups, akin to a first human listening pass. Subsequent stages of clustering refine these categories, utilizing different sets of features to achieve a granularity of annotation that closely mirrors expert human annotation processes. It was found that the acoustic landscape of the GSC was primarily composed of diverse marine mammal sounds, such as fin whale 20 Hz pulses, humpback whale songs, minky whale buzz sequences, sperm whale and dolphin echolocation clicks, and unidentified whale calls. Conversely, the deep-water area off the continental slope featured predominantly fish sounds, chorus-like sounds, and dolphin vocalizations. Detailed analyses of the most prevalent vocalizations are presented, including their bearing-time trajectories and localizations.

Passive ocean acoustic waveguide remote sensing of vocalization behavior and spatial distribution of diverse marine mammal species in the Norwegian and Barents Sea

Leveraging data acquired using a 160-element coherent hydrophone array deployed in the Norwegian and Barents Seas during spring 2014, and the passive ocean acoustic waveguide remote sensing (POAWRS) technique is employed to enable instantaneous wide-area monitoring of marine mammal vocalizations over expanses exceeding 100 km in diameter. The vocalization behavior of diverse marine mammal species including Fin, Humpback, Minke, Sperm, and Beluga whales are analyzed, quantifying time-frequency characteristics and call patterns from their vocalization signals present in high-resolution beamformed power spectrograms. Previously developed automatic detection and machine learning algorithms are employed for clustering and classification of underwater acoustic events, facilitating the subsequent manual audio-visual inspection of whale calls. Bearing-time trajectories of repetitive species-specific vocalizations signals are utilized to estimate locations of the whale calls and hence their temporo-spatial distributions. Through comparative studies, we assess the presence and abundance of marine mammal species-specific vocalization signals in three distinct coastal regions off Norway, namely, Alesund, Lofoten, and Northern Finmark. In addition, we investigate correspondences of marine mammal distributions with concurrently imaged instantaneous wide-area fish distributions from distinct fish species to elucidate potential predator-prey interactions and habitat preferences.

The Effect of Attenuation from Fish on Passive Detection of Sound Sources in Ocean Waveguide Environments

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.

Comparing Performances of Five Distinct Automatic Classifiers for Fin Whale Vocalizations in Beamformed Spectrograms of Coherent Hydrophone Array

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.

Detection, Localization and Classification of Multiple Mechanized Ocean Vessels over Continental-Shelf Scale Regions with Passive Ocean Acoustic Waveguide Remote Sensing

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.

Temporal–spatial, spectral, and source level distributions of fin whale vocalizations in the Norwegian Sea observed with a coherent hydrophone array

AbstractTo better understand fin whale vocalization behaviour in the Norwegian and Barents Seas, a large-aperture densely sampled coherent hydrophone array was deployed in late winter 2014 to monitor their vocalizations instantaneously over wide areas via passive ocean acoustic waveguide remote sensing (POAWRS). Here, we (i) provide a time-frequency characterization for different call types observed (20 Hz pulses, 130 Hz upsweeps, 30–100 Hz downsweep chirps, and 18–19 Hz backbeats); (ii) compare their relative abundances in three different coastal regions off Alesund, Lofoten, and Northern Finnmark; (iii) estimate the temporal and spatial distributions; (iv) source level distributions; and (v) probability of detection (PoD) regions for the more abundant 20 Hz pulse and 130 Hz upsweep call types. The fin whale vocalizations received over the diel cycle (24 h) were significantly more abundant by a factor of roughly seven off Northern Finnmark than the other two regions, associated with fish feeding activities. The source levels are estimated to be 190.5±7.4 dB for the fin whale 20 Hz pulses and 170.3 ± 5.2 dB for the 130 Hz upsweeps. We find that fin whales are capable of producing each vocalization type either independently or simultaneously with other types, and the 20 Hz sound production in the fin whales involves a mechanism that generates a significantly less-intense second-order harmonic of the fundamental.

Comparing passive localization methods for ocean vehicles from their underwater sound received on a coherent hydrophone array

Simultaneous localization and tracking of multiple ocean vehicles over instantaneous continental-shelf scale regions using the passive ocean acoustic waveguide remote sensing (POAWRS) technique employs a large-aperture densely-sampled coherent hydrophone array system to monitor the underwater sounds radiated by ocean vehicles. Here, particle filtering is implemented for bearings-only localization and tracking of surface ships where the estimated bearing-time trajectories of ship-radiated underwater sound detections are used as inputs to provide two-dimensional horizontal position estimates. Coherent beamforming of the acoustic data received on the hydrophone array not only provides estimates of ship bearing, but also significantly enhances the signal-to-noise ratio. Results of passive acoustic surface ship localization and tracking from recordings in the Gulf of Maine and the Norwegian Sea are presented. The particle filtering approach for passive source localization are compared with three other approaches: moving array triangulation (MAT), array invariant (AI), and modified-polar-coordinates extended Kalman filter (MPC-EKF). The passive source localization accuracies, determined by comparison with the GPS-measured position of the surface ships, are dependent on numerous factors such as source-receiver geometry, range, and relative speed. By combining several of these approaches, which have respective pros and cons under different circumstances, the surface ships can be localized with improved accuracy.

Comparing neural networks with conventional classifiers for fin whale vocalizations in beamformed spectrograms of coherent hydrophone array

A large variety of sound sources in the ocean, including biological, geophysical and man-made activities 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-sampled coherent hydrophone array. 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 a large training data set of fin whale and other vocalizations are gathered after manual inspection and labelling. Next, multiple classifiers including neural networks, logistic regression, support vector machine (SVM) and decision tree are built and tested for identifying the fin whale and other vocalizations from the enormous amounts of acoustic signals detected per day. The neural network classifier will use beamformed spectrograms to classify acoustic ...

Temporal-spatial and source level distributions for a repertoire of fin whale vocalizations in the Norwegian Sea observed with a coherent hydrophone array

The vocalizations of the fin whale are detected, characterized and localized over instantaneous wide areas of the Norwegian and Barents Seas using a large-aperture densely-sampled coherent hydrohone array via the passive ocean acoustic waveguide remote sensing (POAWRS) technique from observations in late winter to early spring 2014. The fin whale vocalizations are comprised of their characteristic 20 Hz pulses, interspersed by 130 Hz upsweeps, less abundant 30-100 Hz downsweep chirps and 18-19 Hz centered backbeats. The time-frequency characteristics of these vocalization types and their diel occurrence rate time-series are quantified in three distinct regions of the Norwegian Sea, off the coasts of Alesund, Lofoten, and the Northern Finnmark. Their vocalization rates are a factor of roughly 5 times and 17 times larger respectively for the 20 Hz and 130 Hz centered vocalizations off Northern Finnmark than the other regions. The vocalization rate spatial density distributions, source level distributions an...

Identification of fin whale 20-Hz pulses and other vocalizations from passive monitoring with a coherent hydrophone array

A large variety of sound sources in the ocean, including biological, geophysical and man-made activities 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-sampled coherent hydrophone array. 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 each detected acoustic signal is represented by an amplitude weighted pitch track which describes its fundamental frequency-time and amplitude variation. Multiple features are extracted from the pitch track including mean, minimum and maximum frequencies, bandwidth, signal duration, frequency-time slope and curvature, as well as several amplitude weighted features. A large training data set of fin whale 20-Hz pulses and other vocalizations are gathered after manual inspection and labeling. Next, multiple classifiers including logistic regression and decision tree are built and tested for identifying the fin whale 20-Hz pulses and other vocalizations from the enormous amounts of acoustic signals detected per day. The performance of the classifiers are evaluated and compared

Detection, localization, and classification of multiple ocean vehicles over continental-shelf regions with passive ocean acoustic waveguide remote sensing

Multiple ocean vehicles, including both surface ships and unknown submerged vehicles, can be simultaneously monitored over instantaneous continental-shelf scale regions via passive ocean acoustic waveguide remote sensing (POAWRS) by employing a large-aperture densely sampled coherent hydrophone array system. Here, the approach is demonstrated for multiple merchant ships present in the Norwegian Sea in 2014. The sounds radiated underwater by ocean vehicles, dominated by narrowband tonals and cyclostationary signals, are detected in the beamformed spectrograms. Coherent beamforming of the receiver array data significantly enhances the signal-to-noise ratio of the ship-radiated signals enabling detection of ocean vehicles roughly two orders of magnitude more distant in range than a single hydrophone. The estimated bearing-time trajectory of a sequence of detections are employed to determine the horizontal location of each vehicle using the moving array triangulation technique. The estimated locations are verified by comparison with historical database of merchant ships present in the region. Several time-frequency characteristics are extracted from the detected signals and used to classify and track the ships.

Continental Shelf-Scale Passive Acoustic Detection and Characterization of Diesel-Electric Ships Using a Coherent Hydrophone Array

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.

Instantaneous wide-area passive acoustic monitoring of surface ships and submerged vehicles using a coherent hydrophone array

The ability to monitor surface ships and other ocean vehicles continuously over instantaneous wide areas is essential for a wide range of applications including defense and ocean environmental assessment. Here, we employ a large-aperture coherent hydrophone array system to detect, localize, and classify several surface ships and other ocean vehicles from their sounds radiated underwater using the passive ocean acoustic waveguide remote sensing (POAWRS) technique. The approach is calibrated for four distinct research and fisheries survey vessels with accurately known locations obtained from global positioning systems (GPS). Acoustic signals passively recorded on the coherent hydrophone array are first beamformed for their azimuthal dependencies. The sounds radiated by ocean vehicles are automatically detected using a threshold detector from the beamformed spectrograms. The bearing versus time trajectories of sequences of detections are used to localize the ocean vehicles by employing the moving array triangulation technique. The sounds radiated by the ships are dominated by distinct tonals and cyclostationary signals in the 50 to 2000 Hz frequency range. The temporal-spectral characteristics of these signal can be used to classify each ship. Our analysis indicates the ocean vehicles can be instantaneously monitored and tracked over wide areas spanning more than 300 km in diameter.

Vast assembly of vocal marine mammals from diverse species on fish spawning ground.

Observing marine mammal (MM) populations continuously in time and space over the immense ocean areas they inhabit is challenging but essential for gathering an unambiguous record of their distribution, as well as understanding their behaviour and interaction with prey species. Here we use passive ocean acoustic waveguide remote sensing (POAWRS) in an important North Atlantic feeding ground to instantaneously detect, localize and classify MM vocalizations from diverse species over an approximately 100,000 km(2) region. More than eight species of vocal MMs are found to spatially converge on fish spawning areas containing massive densely populated herring shoals at night-time and diffuse herring distributions during daytime. We find the vocal MMs divide the enormous fish prey field into species-specific foraging areas with varying degrees of spatial overlap, maintained for at least two weeks of the herring spawning period. The recorded vocalization rates are diel (24 h)-dependent for all MM species, with some significantly more vocal at night and others more vocal during the day. The four key baleen whale species of the region: fin, humpback, blue and minke have vocalization rate trends that are highly correlated to trends in fish shoaling density and to each other over the diel cycle. These results reveal the temporospatial dynamics of combined multi-species MM foraging activities in the vicinity of an extensive fish prey field that forms a massive ecological hotspot, and would be unattainable with conventional methodologies. Understanding MM behaviour and distributions is essential for management of marine ecosystems and for accessing anthropogenic impacts on these protected marine species.