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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.

 

The time-dependent spectral characteristics of underwater sound radiated by an ocean vessel has complex dependencies on ship machinery, propeller dynamics, hydrodynamics of ship exhaust and motion, as well as ship board activities. Here the underwater sound radiated by a ship equipped with a controllable pitch propeller (CPP) is analyzed and quantified via its (i) power spectral density for signal energetics, (ii) temporal coherence for machinery tonal sound, and (iii) spectral coherence for propeller amplitude-modulated cavitation noise. Frequency-modulated (FM) tonal signals are also characterized in terms of their frequency variations. These characteristics are compared for different propeller pitch ratios ranging from 20% to 82% at fixed propeller revolutions per minute (RPM). The efficacy and robustness of ship parameter estimation at different pitches are discussed. Finally, analysis of one special measurement is provided, when ship changes speed, propeller pitch and RPM over the duration of the measurement. The 50% pitch is found to be a crucial point for this ship about which tonal characteristics of its underwater radiated sound attain their peak values, while broadband sound and associated spectral coherences are at a minimum. The findings here elucidate the effects of pitch variation on underwater sound radiated by ships with controllable pitch propellers and has applications in ship design and underwater noise mitigation. 

Humpback whale behavior, population distribution and structure can be inferred from long term underwater passive acoustic monitoring of their vocalizations. Here we develop automatic approaches for classifying humpback whale vocalizations into the two categories of song and non-song, employing machine learning techniques. The vocalization behavior of humpback whales was monitored over instantaneous vast areas of the Gulf of Maine using a large aperture coherent hydrophone array system via the passive ocean acoustic waveguide remote sensing technique over multiple diel cycles in Fall 2006. We use wavelet signal denoising and coherent array processing to enhance the signal-to-noise ratio. To build features vector for every time sequence of the beamformed signals, we employ Bag of Words approach to time-frequency features. Finally, we apply Support Vector Machine (SVM), Neural Networks, and Naive Bayes to classify the acoustic data and compare their performances. Best results are obtained using Mel Frequency Cepstrum Coefficient (MFCC) features and SVM which leads to 94% accuracy and 72.73% F1-score for humpback whale song versus non-song vocalization classification, showing effectiveness of the proposed approach for real-time classification at sea. 

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. 

Airgun source systems generate low frequency underwater sound used in reflection and refraction seismology for mapping ocean bottom stratigraphy with important applications in ocean geosciences, such as understanding plate tectonics, ascertaining ocean geological history and climate change, and offshore hydrocarbon prospecting. Seismo-acoustic airgun signals from geophysical surveying activity were recorded at very long ranges, spanning roughly 175-195 km, on a large-aperture densely-populated linear coherent hydrophone array in the Norwegian Sea during Spring 2014. Off the coast of Alesund, airgun signals were detected with 8 s inter-pulse intervals for 3 to 24 hour time periods per day over the 4 days of hydrophone array operation in that region. Here we provide a time-frequency characterization and bearing-time estimation of the received airgun pulses. By correcting for transmission losses in the range- and depth-dependent Norwegian Sea environment, we estimate the source level distribution back projected to a distance of 1 m from the airgun source system. This back-projected source level distribution is then applied to model the Probability of Detection (PoD) region for the airgun signals with the coherent hydrophone array as the receiver in the Norwegian Sea employing the passive ocean acoustic waveguide remote sensing (POAWRS) technique. The estimates of back-projected source level distribution and PoD region provide an understanding of the horizontal spatial propagation extent of the signals from the airgun source system in the shallow and deep water regions of the Norwegian Sea. These results can also be applied to studies of the potential impact of airgun signals on marine organisms. 

An eight-element oil-filled hydrophone array is used to measure the acoustic field in littoral waters. This prototype array was deployed during an experiment between Jeffrey’s Ledge and the Stellwagen Bank region off the coast of Rockport, Massachusetts USA. During the experiment, several humpback whale vocalizations, distant ship tonals and high frequency conventional echosounder pings were recorded. Visual confirmation of humpback moving in bearing relative to the array verifies the directional sensing from array beamforming. During deployment, the array is towed at speeds varying from 4-7 kts in water depths of roughly 100 m with conditions at sea state 2 to 3. This array system consists of a portable winch with array, tow cable and 3 water-resistant boxes housing electronics. This system is deployed and operated by 2 crew members onboard a 13 m commercial fishing vessel during the experiment. Non-acoustic sensor (NAS) information is obtained to provide depth, temperature, and heading data using commercial off the shelf (COTS) components utilizing RS485/232 data communications. Acoustic data sampling was performed at 8 kHz, 30 kHz and 100 kHz with near real-time processing of data and enhanced Signal to Noise Ratio (SNR) from beamforming. The electrical system components are deployed with 3 stacked electronics boxes housing power, data acquisition and data processing components in water resistant compartments. A laptop computer with 8 TB of external storage and an independent Global Positioning System (GPS) antenna is used to run Passive Ocean Acoustic Waveguide Remote Sensing (POAWRS) software providing beamformed spectrogram data and live NAS data with capability of capturing several days of data. The acquisition system consists of Surface Mount Device (SMD) pre-amplifiers with filter to an analog differential pair shipboard COTS acquisition system. Pre-amplifiers are constructed using SMD technology where components are pressure tolerant and potting is not necessary. Potting of connectors, electronics and hydrophones via 3D printed molding techniques will be discussed. Array internal components are manufactured with Thermoplastic Polyurethane (TPU) 3D printed material to dampen array vibrations with forward and aft vibration isolation modules (VIM). Polyurethane foam (PUF) used to scatter breathing waves and dampen contact from wires inside the array without attenuating high frequencies and allowing for significant noise reduction. A single Tygon array section with a length of 7.5 m and diameter of 38 mm contains 8 transducer elements with a spacing of 75 cm (1 kHz design frequency). Pre- amplifiers and NAS modules are affixed using Vectran and steel wire rope positioned by swaged stops along the strength member. The tow cable length is 100 m with a diameter of 22 mm that is potted to a hose adapter to break out 12 braided copper wire twisted pair conductors and terminates the tow cable Vectran braid. This array in its current state of development is a low-cost alternative to obtain quality acoustic data from a towed array system. Used here for observation of whale vocalizations, this type of array also has many applications in military sonar and seismic surveying. Maintenance on the array can be performed without the use of special facilities or equipment for dehosing and conveniently uses castor oil as an environmentally safe pressure compensating and coupling fluid. Array development including selection of transducers, NAS modules, acoustic acquisition system, array materials and method of construction with results from several deployments will be discussed. We also present beamformed spectrograms containing humpback whale downsweep moans and underwater blowing (bubbles) sounds associated with feeding on sand lance (Ammodytes dubius). 

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. 

The wide‐area group behaviour of spawning Atlantic cod and herring is investigated. By a combination of Ocean Acoustic Waveguide Remote Sensing (OAWRS) and conventional sensing methods, first‐look images of the instantaneous population density are obtained of entire Atlantic cod spawning groups, stretching for tens of kilometres in the Nordic Seas. This structural information made it possible to quantify the spawning group size distribution of cod over a roughly 30‐year period from conventional line‐transect data acquired annually by vertical echo sounding in the Nordic Seas. The size distribution is found to be consistent with the log‐normal probability density often found in growth processes that depend on many independent parameters. Nordic Seas cod populations are found to distribute into many vast behavioural groups during spawning with relatively stable mean size despite larger variations in total annual population. When sustained at pre‐industrial levels, the total spawning population is found to greatly exceed the mean spawning group size. As an apparent consequence of this large differential, when the total population, or overall scale, declined to within a standard deviation of this mean cod spawning group quantum, or inner‐group‐behavioural scale, return to pre‐industrial levels required decades. Findings for Atlantic herring are similar, where summing the spawning group populations measured in a single instantaneous OAWRS image per day over the 8‐day peak spawning period enabled accurate enumeration of the entire Georges Bank herring spawning population to within 7% of the independent NOAA estimate for 2006. These results may be relevant to other oceanic fish.