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Acoustic propagation is significantly impacted by seabed characteristics, which play a large role in propagation modeling. Shallow seabed characteristics comprise a notable area of research due to their impacts on bottom loss, but deep seabed characteristics are often ignored. At low frequencies (several hundred Hertz, particularly below 100 Hz) and at ranges less than that corresponding to the seafloor critical angle, these deep layer characteristics have non-negligible effects. Those effects are explored here using a subset of data from a marine seismic reflection survey, MGL2104, in an environment with a nearly constant ∼2.6 km bathymetry. The source is a 5700 in.3 airgun array and reflections are measured by a 1200 channel, ∼15 km streamer, with both arrays at 12 m depth. The results show that in one-third–octave bands below 100 Hz, a significant fraction of the reflected energy (sometimes >50%) at certain ranges in the water column is attributable to sub-seabed layers, and the seafloor reflections only become the dominant source at ranges where the reflection path approaches a critical angle. The analysis also considers the effects of layer depths on reflected energy, demonstrating that increased depth does not necessarily correlate with decreased energy reflected in the water column. [ABSTRACT FROM AUTHOR]

The coherent recombination of a direct and seabed reflected path is sensitive to the geophysical properties of the seabed. The concept of feature-based inversion is used in the analysis of acoustic data collected on a vertical line array (VLA) on the New England continental shelf break in about 200 m of water. The analysis approach for the measurements is based on a ray approach in which a direct and bottom reflected path is recombined, resulting in constructive and destructive interference of the acoustic amplitudes with frequency. The acoustic features have the form of prominent nulls of the measured received levels as a function of frequency as a broadband (500–4500 Hz) source passes the closest point of approach to the VLA. The viscous grain shearing (VGS) model is employed to parameterize a two-layer seabed model. The most likely seabed is a sand sediment with a porosity of about 0.42. There is a possibility of a thin (less than 0.5 m) surface layer having a slightly higher porosity between 0.45 and 0.50. Using the estimates for the VGS parameters inferred from the short-range frequency features, a normal mode model is used to predict the received acoustic levels over larger range scales. [ABSTRACT FROM AUTHOR]

An efficient and precise time-frequency analysis method for real-time ocean bottom seismometer (RTOBS) data in the South China Sea (SCS) is presented. Overcoming the limitations of conventional methods, the method involves temporal segmentation, unique frequency octaves, and Fourier transforms to generate power spectral density (PSD) and probability density function profiles. The method demonstrates superior precision, computational efficiency, and full-bandwidth (0 to Nyquist) capability compared to traditional techniques, as validated through theoretical and empirical evaluations. Applied to SCS RTOBS data, it unveils temporal PSD variations, shedding light on underwater noise sources like earthquakes, offshore blasting, ship-induced disturbances, and tidal effects. Establishing background noise levels in the SCS supports noise source categorization and ocean environment monitoring. Furthermore, comparing onshore and offshore seismic stations advances interdisciplinary research, fostering a comprehensive understanding of acoustics and seismology in the region. [ABSTRACT FROM AUTHOR]

The conversion from seismic to ocean-acoustic waves occurs in different places on the bottom of the ocean, often hundreds to thousands of kilometers away from the epicenter. Here, we investigate this conversion process by studying 15 large-magnitude earthquakes that occurred between 2014 and 2022 along the Kermadec Arc in the southwestern Pacific Ocean. To pinpoint the location where seismic-to-acoustic conversion takes places, we analyze hydroacoustic signals recorded by a hydrophone triplet station of the International Monitoring System in the Juan Fernández archipelago. Results from direction-of-arrival and travel-time calculations indicate that the location of the conversion zone largely matches segments of the Louisville Seamount Chain, its lateral extent ranging from approximately 300 to 1800 km, and its location depending on the geometry between earthquake epicenter and the seamounts. [ABSTRACT FROM AUTHOR]

An ocean acoustics experiment in 2017 near a shipping lane on the New England continental shelf in about 75 m of water provided an opportunity to evaluate a methodology to extract source signatures of merchant ships in a bottom-limited environment. The data of interest are the received acoustic levels during approximately 20 min time intervals centered at the closest position of approach (CPA) time for each channel on two 16-element vertical line arrays. At the CPA ranges, the received levels exhibit a frequency-dependent peak and null structure, which possesses information about the geophysical properties of the seabed, such as the porosity and sediment thickness, and the characterization of the source, such as an effective source depth. The modeled seabed is represented by two sediment layers, parameterized with the viscous grain shearing (VGS) model, which satisfies causality, over a fixed deep layered structure. Inferred estimates of the implicit source levels require averaging an error function over the full 20 min time intervals. Within the 200–700 Hz band, the Wales–Heitmeyer model captures the inferred frequency dependence of the source levels. [ABSTRACT FROM AUTHOR]

Ocean bottom seismometer networks can record opportunistic data sets of 20-Hz fin whale calls. Because networks are often too sparse for multi-station tracking, single-station methods are needed to estimate call density. We investigated a method to range to singing fin whales at full ocean depths using the spacing of water column multiples. Calls were detected by cross-correlating a spectrogram with a template call. To enhance multipath signals, we considered 20-min windows and either summed the spectrograms of all calls aligned on the strongest detection before measuring the multipath spacing or measured the spacing directly from the autocorrelation of the cross correlation time series. We evaluated the methods at five sites with contrasting seafloor and subsurface properties, bathymetric relief, and water depths of 4000–6000 m, using fin whale songs at four sites and a sei whale song at the fifth. The autocorrelation method works best, and ranges can be obtained to >15 km. Ranging at sedimented sites requires careful accounting for subsurface reflections. Ranges have considerable uncertainty in regions of bathymetric relief. The method requires that the time between calls is different from that of the multipaths and does not work reliably when more than one whale is singing nearby. [ABSTRACT FROM AUTHOR]

In deep water, deploying a short vertical line array (VLA) is an effective way for source localization. In the past decade, most studies focused on localizing sources at the short to moderate ranges in the reliable acoustic path or the direct arrival zone (DAZ), with a VLA deployed near the ocean bottom. Little work has been done for the end part of the DAZ and the zones outside the DAZ. In addition, a VLA deployed at other depths rather than near the bottom is rarely studied. This paper proposes a near-surface source depth estimation method by matching the measured time delay with a library of modeled values under different source depths calculated by a simple formula. This method is suitable for zones, which contains two paths (one is reflected from the sea surface) with very close arrival angles, of a VLA deployed not only near the bottom, but also at other depths of the water column. Source depth estimation strategy for the end part of each zone, which faces the problem of poor depth resolution, is also analyzed. Simulation and experimental data of the airgun and explosive sources in the South China Sea are used to demonstrate the method. [ABSTRACT FROM AUTHOR]

Broadband acoustic analysis of scattering from sharp density gradients in the water column generally treat the interfaces as smooth surfaces. However, these interfaces may exhibit roughness owing to external water column forcing and local convective processes. In this work we extend broadband backscatter analysis methods to consider interface roughness by drawing upon methods developed for sea surface and seabed acoustic backscattering. The one-dimensional acoustic model from Weidner and Weber [J. Acoust. Soc. Am. 150(6), 4353–4361 (2021)], which predicts a decay in the reflected wave amplitude from stratification interfaces with increasing frequency, was expanded for surface applications. The expanded model was used to analyze the scattered pressure field from interfaces over a range of surface roughness magnitudes. Analysis of model results indicate that stratification interface roughness, quantified by the root-mean-squared interface slope angle and root-mean-squared height of the interface, modifies the model-predicted frequency-dependent backscattering. A broadband acoustic inversion procedure to remotely measure the magnitude of the vertical extent of stratification gradients and the corresponding sound speed perturbation was defined. The broadband inversion method was tested on data collected in the Baltic Sea with well-documented, strong salinity-driven stratification. [ABSTRACT FROM AUTHOR]

The received reverberation signal can be beamformed by utilizing a vertical array, generating a vertical-angle time record (VATR) that enables analysis of spatiotemporal distribution characteristics. Due to the influence of multipath propagation effects, deep-sea reverberation exhibits highly complex characteristics, especially in a seabed with significant depth variation. In a recent bistatic reverberation experiment with a vertical array receiver, peculiar bright stripes were observed in the VATR. These stripes are the result of scattering caused by large-scale bottom structures and are closely associated with seamounts. To accurately model and interpret these stripes, a bistatic reverberation model is initially established to reproduce the VATR. This model enables us to numerically simulate the spatiotemporal distribution of reverberation in the VATR, offering a qualitative explanation for these stripes. However, the model alone is incapable of predicting the specific stripe structure associated with a particular seamount. To address this limitation, an equation system is introduced to calculate the stripe parameters based on the seamount parameters. By analyzing and deducing the dependency of the stripes on the seamount, conclusions were drawn using the equation system. Ultimately, the presented model and equation system successfully reproduce and comprehensively explain the observed abnormal stripes from the experiment. [ABSTRACT FROM AUTHOR]

Performing reproducible vessel source level (SL) measurements is complicated by seabed reflections in shallow water. In deep water, with a hydrophone far from the seabed, it is straightforward to estimate propagation loss (PL) and convert sound pressure level (SPL) into SL using the method codified in the international standard ISO 17208-2 [International Organization for Standardization (ISO), Geneva, Switzerland (2019)]. Estimating PL is more difficult in shallow water because of the way that sound reflects from the seabed such that multiple propagation paths contribute to SPL. Obtaining reproducible SL measurements in shallow water requires straightforward and robust methods to estimate PL. From May to July 2021, a field experiment evaluated different methods of measuring vessel SL in shallow water. The same vessels were measured many times in water depths of 30, 70, and 180 m. In total, 12 079 SL measurements were obtained from 1880 vessel transits and 16 hydrophones, distributed across 3 moored vertical line arrays and 2 moored horizontal line arrays. The experiment confirmed that it is possible to obtain reproducible vessel SL estimates in shallow water comparable to within ±2.5 dB of ISO-compliant measurements in deep water and repeatable to within ±1.5 dB. [ABSTRACT FROM AUTHOR]

Observed near the seafloor, broadband noise emissions from a vessel passing directly above exhibit frequency bands where potential acoustic energy is greater than kinetic energy while the opposite occurs in neighboring frequency bands. The condition where the dynamic and kinematic energy forms differ in this manner is characteristic to interference involving steep angles or near-normal incidence reflection from the seafloor. Measurements are made at two experimental sites using a research vessel passing above a vector sensor, positioned ∼1.5 m above the seabed, resulting in a vessel horizontal range approaching ∼0. The data are expressed as a ratio of kinetic to potential energy in decibels and yield information on seabed properties. A model for kinetic and potential energy is developed from the method of images using a layered seabed and is used to invert data collected in Puget Sound. A higher-impedance seabed is identified via inversion, which is consistent with the thin Holocene sediments in the region. For data collected on the New England Mud Patch, the model is instead applied directly to nominal seabed parameters originating from prior studies that identify a low-speed mud layer atop a higher-speed transition layer separating the mud substrate from a sediment basement. [ABSTRACT FROM AUTHOR]

A seismic reflection survey conducted directly over two bottom-mounted hydrophones in the north-east Pacific Ocean is used to explore how surface source locations affect ambient noise interferometry for the two hydrophones. The airgun shots are used as an approximation of an impulsive sound source at a discrete location, which allows us to investigate spatial contributions to the cross correlation between the two hydrophones. Simulated and experimental results are presented. The contributions to the cross correlations are explained by different reflections off the surface or bottom of the ocean, and a discussion about what can and cannot be inferred about the emergence to the Green's function is presented. [ABSTRACT FROM AUTHOR]

Underwater noise transmission in the ocean environment is a complex physical phenomenon involving not only widely varying physical parameters and dynamical scales but also uncertainties in the ocean parameters. It is challenging to construct generalized physical models that can predict transmission loss in a broad range of situations. In this regard, we propose a convolutional recurrent autoencoder network (CRAN) architecture, which is a data-driven deep learning model for learning far-field acoustic propagation. Being data-driven, the CRAN model relies only on the quality of the data and is agnostic to how the data are obtained. The CRAN model can learn a reduced-dimensional representation of physical data and can predict the far-field acoustic signal transmission loss distribution in the ocean environment. We demonstrate the ability of the CRAN model to learn far-field transmission loss distribution in a two-dimensional ocean domain with depth-dependent sources. Results show that the CRAN can learn the essential physical elements of acoustic signal transmission loss generated due to geometric spreading, refraction, and reflection from the ocean surface and bottom. Such ability of the CRAN to learn complex ocean acoustics transmission has the potential for real-time far-field underwater noise prediction for marine vessel decision-making and online control. [ABSTRACT FROM AUTHOR]

We investigate the feasibility of using a known elastic target located near the seabed for the purpose of inferring characteristics of marine sediment. In the problem considered the object position and its burial depth are not known with precision. First, the admittance matrix of the elastic object is determined (numerically or experimentally) over a wide frequency range in the structural acoustic regime. Then, the equivalent source method (ESM) coupled with a spectral representation of the Green's functions in stratified domains is used to predict the object acoustic signature in various environments and experimental configurations. The resulting solver takes into account all multiple scattering between target (buried or not), sea floor, and sea surface and is not limited to short distances. After presenting the solution to the forward problem several synthetic inversions for sediment characteristics are shown. They are based upon a resonance-based misfit function we describe. The Bayesian procedure also infers object burial and source-object range, broadening its range of application. [ABSTRACT FROM AUTHOR]

This is an investigation of sound propagation over a muddy seabed at low grazing angles. Data were collected during the 2017 Seabed and Bottom Characterization Experiment, conducted on the New England Mud Patch, a 500 km2 area of the U.S. Eastern Continental Shelf characterized by a thick layer of muddy sediments. Sound Underwater Signals (SUS), model Mk64, were deployed at ranges of 1–15 km from a hydrophone positioned 1 m above the seafloor. SUS at the closest ranges provide measurements of the bottom reflection at low grazing angles (<3 deg). Broadband analysis from 10 Hz to 10 kHz reveals resonances in the bottom reflected signals. Comparison of the measurements to simulated signals suggest a surficial layer of mud with a sound speed lower than the underlying mud and overlying water. The low sound speed property at the water–mud interface, which persists for less than 1 m, establishes a sound duct that impacts mid-frequency sound propagation at low grazing angles. The presence of a low-speed surficial layer of mud could be universal to muddy seabeds and, hence, has strong implications for mid-frequency sound propagation wherever mud is present. [ABSTRACT FROM AUTHOR]

This paper discusses the nature of the low-frequency seismo-acoustic waves generated by submarine earthquakes in the ocean. In a finite-depth homogeneous ocean over a semi-infinite solid crust, the derivation of the acoustic equations shows that waves propagate as modes. The waves propagating with the speed of sound in water (T waves) are preceded by waves with frequencies below the Airy phase. Furthermore, the group speeds of these modes are sensitive to the environmental setting. As a test, we applied the spectral finite-element code SPECFEM2D in a simplified configuration with an ocean layer overlaying a solid crust, and a seismic source below a Gaussian seamount surrounded by a flat seafloor. The simulations confirm that the generated T waves and their precursors follow the theoretical dispersion curves. A more realistic environment with a seismically-layered crust and a sound-speed profile in the ocean is then used to predict the expected acoustic modes. Although noisy, recordings by ocean bottom seismometers from the southwest Indian Ocean show T waves preceded by ultra-low frequency waves, which display two modes comparable to the theoretical ones. They are in good agreement for mode 1, whereas, for mode 0, a slight offset in frequency has yet to be explained. [ABSTRACT FROM AUTHOR]

Acoustic data were recorded on two vertical line arrays (VLAs) deployed in the New England Mud Patch during the Seabed Characterization Experiment 2017 in about 75 m of water. The sound recorded during the passage of merchant ships permits identification of singular points for the waveguide invariant β for mode pairs (1 , n) : β 1 , n , for n = 2 , 3 , 4 , 5 , in the 15–80 Hz band. Using prior geophysical information and an acoustic data sample from the merchant ship KALAMATA, a geoacoustic model M of the seabed was developed. Then, using data samples from other merchant ships, a feature-ensemble maximum entropy method is employed to infer the statistical properties of geoacoustic parameter values for the sound speeds in a surface mud layer and a deep sand layer. Technical challenges include a sparsity of observed singular points, the unique identification of mode pairs for an observed singular point, and the deviation of the waveguide from horizontal stratification. A geoacoustic model M is developed that reproduced the observed β ≈ − 1 for f < 20 Hz and mode cutoff features at about 15 Hz. The statistical low-frequency inference of the singular point structure from multiple ships provides evidence of an angle of intromission at the water sediment interface with an average sound speed ratio of about 0.986 and an average sound speed for the deeper sand layer of about 1775 m/s. [ABSTRACT FROM AUTHOR]

This work demonstrates that automated mine countermeasure (MCM) tasks are greatly facilitated by characterizing the seafloor environment in which the sensors operate as a first step within a comprehensive strategy for how to exploit information from available sensors, multiple detector types, measured features, and target classifiers, depending on the specific seabed characteristics present within the high-frequency synthetic aperture sonar (SAS) imagery used to perform MCM tasks. This approach is able to adapt as environmental characteristics change and includes the ability to recognize novel seabed types. Classifiers are then adaptively retrained through active learning in these unfamiliar seabed types, resulting in improved mitigation of challenging environmental clutter as it is encountered. Further, a segmentation constrained network algorithm is introduced to enable enhanced generalization abilities for recognizing mine-like objects from underrepresented environments within the training data. Additionally, a fusion approach is presented that allows the combination of multiple detectors, feature types spanning both measured expert features and deep learning, and an ensemble of classifiers for the particular seabed mixture proportions measured around each detected target. The environmentally adaptive approach is demonstrated to provide the best overall performance for automated mine-like object recognition. [ABSTRACT FROM AUTHOR]

Merchant ship-radiated noise, recorded on a single receiver in the 360–1100 Hz frequency band over 20 min, is employed for seabed classification using an ensemble of deep learning (DL) algorithms. Five different convolutional neural network architectures and one residual neural network are trained on synthetic data generated using 34 seabed types, which span from soft-muddy to hard-sandy environments. The accuracy of all of the networks using fivefold cross-validation was above 97%. Furthermore, the impact of the sound speed and water depth mismatch on the predictions is evaluated using five simulated test cases, where the deeper and more complex architectures proved to be more robust against this variability. In addition, to assess the generalizability performance of the ensemble DL, the networks were tested on data measured on three vertical line arrays in the Seabed Characterization Experiment in 2017, where 94% of the predictions indicated that mud over sand environments inferred in previous geoacoustic inversions for the same area were the most likely sediments. This work presents evidence that the ensemble of DL algorithms has learned how the signature of the sediments is encoded in the ship-radiated noise, providing a unified classification result when tested on data collected at-sea. [ABSTRACT FROM AUTHOR]

A three-dimensional (3D) finite difference (FD) model with formal fourth-order accuracy has been developed for the ocean acoustic Helmholtz equation (HE), which can be used to address arbitrary bathymetry and provide more accurate benchmark solutions for other 3D underwater acoustic approximate models. The derivatives in the acoustic HE are numerically discretized based on regular grids, and the perfectly matched layer is introduced to absorb unphysical reflections from the boundaries where Sommerfeld radiation conditions are deployed. The system of linear equations is solved using a parallel matrix-free geometric multigrid preconditioned biconjugate gradient stabilized iteration method, and the code (named COACH) is run on the Tianhe-2 supercomputer in China. Four 3D topographic benchmark acoustic cases—a wedge waveguide, Gaussian canyon, conical seamount, and corrugated seabed—are simulated to test the present FD model, and the maximum number of grid points reaches 33.15 × 109 in the wedge waveguide case, running in parallel with 988 central processing unit cores. Furthermore, the accuracy and generality of the present model have been verified by solution comparisons with other available 3D acoustic propagation models, and the two-dimensional and 3D transmission loss contours are presented to facilitate the distinguishing among the acoustic field features of these cases. [ABSTRACT FROM AUTHOR]

A multitask convolutional neural network (CNN) is trained to localize the instantaneous position of a motorboat throughout its transit past a wide aperture linear array of hydrophones located 1 m above the sea floor in water 20 m deep. A cepstrogram database for each hydrophone and a cross-correlogram database for each pair of adjacent hydrophones are compiled for multiple motorboat transits. Cepstrum-based and correlation-based feature vectors (along with ground-truth source bearing and range data) form the inputs to train three CNNs so that they can predict the instantaneous source range and bearing for other "unseen" motorboat transits. It is shown that CNNs operating on multi-sensor cepstrum-based feature maps are able to predict the instantaneous range and bearing of a transiting motorboat, even when the source is near an endfire direction. Also, multi-sensor generalised cross correlation-based feature maps are able to predict the range and bearing of a transiting motorboat in the presence of interfering multipath arrivals. When compared with the cepstrum-only CNN, cross correlation-only CNN, and the conventional model-based method of passive ranging by wavefront curvature, the combined cepstrum-cross correlation CNN is shown to provide superior source localization performance in a multipath underwater acoustic environment. [ABSTRACT FROM AUTHOR]

An examination of the received spectrogram levels of about twenty merchant ship recordings on two vertical line arrays deployed on the New England continental shelf during the Seabed Characterization Experiment 2017 has identified an acoustic feature that can be attributed to the group velocities of modes 1 and 2 being equal at a frequency f = F. The observation of such a feature is a result of β n m (2 π F) = ∞ , where βnm is the waveguide invariant for modes n and m. For the New England Mudpatch, the average value of F is about 24.5 Hz. An effective seabed model is inferred from a feature inversion method that has a deep sediment layer which lies between 190 m and 290 m beneath the seafloor with sound speeds on the order of 1810 m/s. This effective sediment model appears to be consistent with a previous seismic survey on the New England shelf that identified a deep low speed layer about 250 m beneath the water sediment interface. [ABSTRACT FROM AUTHOR]

This paper describes a shallow water range-dependent propagation model (RPM) based on the equivalent source method (ESM). The proposed model allows both the sea surface and fluid seabed to vary with the propagation range. The proposed equivalent source method-based range-dependent propagation model (ESM-RPM) utilizes three sets of equivalent sources, placed above the sea surface, below the seabed, and above the seabed, which replace the sea surface reflection, seabed reflection, and seabed transmission, respectively. The unknown strengths of the equivalent sources can be determined by solving an inverse problem based on the boundary conditions. The capability of the ESM-RPM for propagation in refractive water is demonstrated by evaluating the Green's function using a modal projection method. Numerical simulations are conducted in iso-velocity and refractive shallow water with an underwater canyon and corrugated surface waves, including two-dimensional (2-D) propagation across the canyon and three-dimensional (3-D) propagation along the canyon. Further simulations demonstrate the 2-D across-canyon and 3-D along-canyon propagations with random rough sea surfaces. The results show that the proposed ESM-RPM provides efficient, benchmark-quality numerical solutions that accurately capture the mode coupling associated with the varying cross section of the waveguide. Thus, the model has great potential to be applied in benchmarking propagation in shallow water with the varying sea surface and seabed. [ABSTRACT FROM AUTHOR]

While source localization and seabed classification are often approached separately, the convolutional neural networks (CNNs) in this paper simultaneously predict seabed type, source depth and speed, and the closest point of approach. Different CNN architectures are applied to mid-frequency tonal levels from a moving source recorded on a 16-channel vertical line array (VLA). After training each CNN on synthetic data, a statistical representation of predictions on test cases is presented. The performance of a single regression-based CNN is compared to a multitask CNN in which regression is used for the source parameters and classification for the seabed type. The impact of water sound speed profile and seabed variations on the predictions is evaluated using simulated test cases. Environmental mismatch between the training and testing data has a negative impact on source depth estimates, while the remaining labels are estimated tolerably well but with a bias towards shorter ranges. Similar results are found for data measured on two VLAs during Seabed Characterization Experiment 2017. This work shows the superiority of multitask learning and the potential for using a CNN to localize an acoustic source and detect the surficial seabed properties from mid-frequency sounds. [ABSTRACT FROM AUTHOR]

The under-ice acoustic transmission experiment of 2013, conducted under ice cover in the Fram Strait, was analyzed for bottom interactions for the purpose of developing a model of the seabed. Using the acoustic signals, as well as data from other sources, including cores, gravimetric, refraction, and seismic surveys, it was deduced that the seabed may be modeled as a thin surficial layer overlaid on a deeper sediment. The modeling was based on the Biot–Stoll model for acoustic propagation in porous sediments, aided by more recent developments that improve parameter estimation and depth dependence due to consolidation. At every stage, elastic and fluid approximations were explored to simplify the model and improve computational efficiency. It was found the surficial layer could be approximated as a fluid, but the deeper sediment required an elastic model. The full Biot–Stoll model, while instrumental in guiding the model construction, was not needed for the final computation. The model could be made to agree with the measurements by adjusting the surficial layer thickness. [ABSTRACT FROM AUTHOR]

Very-low-frequency (VLF) sound has significant potential for underwater detection and estimation of geoacoustic models of the ocean bottom structure. In marine settings, one type of VLF sound is the interface wave. These waves, trapped near the fluid–solid interface, are called Scholte waves, and this is the subject of this study. A field experiment was carried out in the South China Sea with the objective of exciting Scholte waves and investigating the propagation. The data were acquired by an ocean bottom seismometer, deployed on the seafloor. A large volume airgun array near the sea surface provided the sound source. The fundamental and three higher-order mode Scholte waves were excited. The Scholte waves are investigated by seismograms and a phase velocity inversion. The observed frequencies are in the range of 1.0–2.9 Hz. The energy attenuation is proportional to 1 / r at the peak frequency 1.4 Hz. The shear wave speed structure, down to 600 m beneath the seafloor, is revealed from the dispersion curves by a least-squares inversion algorithm. The inversion result shows that the shear wave speed is below 300 m/s in the uppermost layer, which explains well the weak excitation of Scholte waves in this experiment. [ABSTRACT FROM AUTHOR]

In the viscous grain shearing (VGS) theory of wave propagation in an unconsolidated sediment, the dispersion formulas for the phase speed and attenuation of the compressional and shear wave involve two parameters, the compressional modulus, γp, and the shear modulus, γs, which depend on the radius of the circle of contact between contiguous grains in the granular medium. The radius of contact itself depends on the overburden pressure, and hence depth, in the sediment. Based on these observations, the VGS theory is extended to create a geo-acoustic model of a horizontally stratified sediment in which each layer has a uniform porosity, bulk density, and mean grain size, all of which are assumed known from geological survey data. In a given layer, the overburden pressure consists of the contributions from all the higher layers. From the overburden pressure, the compressional and shear moduli are expressed as functions of depth throughout the layer, thereby allowing the frequency dependent phase speed and attenuation profiles of both types of wave to be computed from the VGS dispersion formulas. To illustrate the VGS geo-acoustic modeling technique, two examples are discussed, one of which represents the mud overlying sand sediment at the New England Mud Patch. [ABSTRACT FROM AUTHOR]

In this work, model-based methods are employed, along with machine learning techniques, to classify sediments in oceanic environments based on the geoacoustic properties of a two-layer seabed. Two different scenarios are investigated. First, a simple low-frequency case is set up, in which the acoustic field is modeled with normal modes. Four different hypotheses are made for seafloor sediment possibilities, and these are explored using both various machine learning techniques and a simple matched-field approach. For most noise levels, the latter has an inferior performance to the machine learning methods. Second, the high-frequency model of the scattering from a rough, two-layer seafloor is considered. Again, four different sediment possibilities are classified with machine learning. For higher accuracy, one-dimensional convolutional neural networks are employed. In both cases, the machine learning methods, both in simple and more complex formulations, lead to effective sediment characterization. The results assess the robustness to noise and model misspecification of different classifiers. [ABSTRACT FROM AUTHOR]

Although matched-field geoacoustic inversion (MFI) has been successfully applied for seabed sediment parameters, its estimation capabilities are limited due to the range dependence of ocean sound-speed profiles, bathymetry, and bottom sediment. This paper proposes a method called propagation invariant (PI). As a purely data-driven method, PI eliminates the effect of intervening range-dependent variations on acoustic propagation and depends only on the "local" environmental characteristics, thus providing ideal input data for MFI. In this paper, the PI concept is applied for MFI in a range-dependent environment by simulations. Results show good MFI performance even for a highly range-dependent waveguide. [ABSTRACT FROM AUTHOR]

In ocean acoustics, many types of optimizations have been employed to locate acoustic sources and estimate the properties of the seabed. How these tasks can take advantage of recent advances in deep learning remains as open questions, especially due to the lack of labeled field data. In this work, a Convolutional Neural Network (CNN) is used to find seabed type and source range simultaneously from 1 s pressure time series from impulsive sounds. Simulated data are used to train the CNN before application to signals from a single hydrophone signal during the 2017 Seabed Characterization Experiment. The training data includes four seabeds representing deep mud, mud over sand, sandy silt, and sand, and a wide range of source parameters. When applied to measured data, the trained CNN predicts expected seabed types and obtains ranges within 0.5 km when the source-receiver range is greater than 5 km, showing the potential for such algorithms to address these problems. [ABSTRACT FROM AUTHOR]

This paper applies a non-linear Bayesian marginalization approach to ship spectral source level estimation in shallow water with unknown seabed properties and uncertain source depth. The algorithm integrates the posterior probability density over seabed models sampled via trans-dimensional Bayesian matched-field inversion and over depths/ranges of multiple point sources (representing different noise-generating components of a large ship) via Metropolis-Hastings sampling. Source levels and uncertainty are derived from marginal distributions for source strength. The approach is applied to radiated noise due to a container ship recorded on a bottom-moored horizontal array in shallow water. The average uncertainty is 3.8 dB/Hz for tonal frequencies. [ABSTRACT FROM AUTHOR]

Fin whales were once abundant in the seas to the southwest of Portugal, but whaling activities decreased their numbers considerably. Acoustic data from ocean bottom seismometers provide an opportunity to detect fin whales from their notes, data that would otherwise be logistically challenging and expensive to obtain. Based on inter-note interval and frequency bandwidth, two acoustic patterns produced by fin whales were detected in the study area: pattern 1, described from fin whales in the Mediterranean Sea, and pattern 2, associated with fin whales from the northeast North Atlantic Ocean (NENA). NENA fin whales travel into the western Mediterranean Sea, but the Mediterranean population has not been documented to travel regularly into the NENA. In this study, 11 months of acoustic data recorded southwest of Portugal in the NENA were used to characterize 20-Hz fin whale notes into these patterns. Pattern 2 was the most common and occurred mostly in November–January. Pattern 1 occurred less frequently and mostly in September–December, February and April, which suggested a limited excursion of whales from the Mediterranean Sea. There were also occasions when the two patterns were recorded simultaneously. Results suggest that fin whales from the NENA and Mediterranean Sea might mix in the area during part of the year. [ABSTRACT FROM AUTHOR]

Broadband data acquired during the Modal Mapping Experiment (MOMAX) V experiment are used to invert simultaneously for the three-dimensional (3D) water column sound speed profiles and the compressional wave speed and density profiles of the seabed in shallow waters off the coast of New Jersey. Linear Frequency Modulation sweep signals in the band 50–300 Hz are transmitted from a nearly stationary source at several discrete positions to a set of freely drifting receivers. Mode travel times are estimated from the signals acquired by the drifting buoys, and these are then used as input data in an inversion algorithm that estimates the acoustic properties of the water column and sediments. The resulting 3D compressional wave speed profiles in the seabed are generally consistent with the one-dimensional profile obtained during the narrowband component of MOMAX V, as well as the results from other experiments in the same area. The validity of the inversion results has also been assessed by the ability of the inverted model to predict the fields measured during the narrowband experiments. [ABSTRACT FROM AUTHOR]

The ray-based blind deconvolution algorithm can provide an estimate of the channel impulse responses (CIRs) between a shipping source of opportunity and the elements of a receiving array by estimating the unknown phase of this random source through wideband beamforming along a well-resolved ray path. However, due to the shallow effective depth (typically <10 m) and low frequency content (typically less than a few kHz) associated with shipping sources, the interfering direct and surface arriving pair and subsequent bottom and surface-bottom arrival pair cannot always be resolved in the CIR arrival-time structure. Nevertheless, this study demonstrates that the bottom reflection loss can be inferred from the ratio of the magnitude spectra of these two arrival pairs if a frequency-dependent correction (which can be purely data based) is applied to correct for the dipole source effect. The feasibility of the proposed approach is demonstrated to invert for the geoacoustic parameters of a soft-layer covering the ocean floor using a nonlinear least-square algorithm. [ABSTRACT FROM AUTHOR]

Extraction of tonal signals embedded in background noise is a crucial step before classification and separation of low-frequency sounds of baleen whales. This work reports results of comparing five tonal detectors, namely the instantaneous frequency estimator, YIN estimator, harmonic product spectrum, cost-function-based detector, and ridge detector. Comparisons, based on a low-frequency adaptation of the Silbido scoring feature, employ five metrics, which quantify the effectiveness of these detectors to retrieve tonal signals that have a wide range of signal to noise ratios (SNRs) and the quality of the detection results. Ground-truth data were generated by embedding 20 synthetic Antarctic blue whale (Balaenoptera musculus intermedia) calls in randomly extracted 30-min noise segments from a 79 h-library recorded by an Ocean Bottom Seismometer in the Indian Ocean during 2012–2013. Monte-Carlo simulations were performed using 20 trials per SNR, ranging from 0 dB to 15 dB. Overall, the tonal detection results show the superiority of the cost-function-based and the ridge detectors, over the other detectors, for all SNR values. More particularly, for lower SNRs (⩽ 3 dB), these two methods outperformed the other three with high recall, low fragmentation, and high coverage scores. For SNRs ⩾ 7 dB, the five methods performed similarly. [ABSTRACT FROM AUTHOR]

Marine sediment properties exhibit fluctuations on a very wide range of scales in all three spatial dimensions. These fluctuations lead to scattering of acoustic waves. Seabed scattering models that treat such fluctuations are reasonably well developed under the plane-wave assumption. A recent model, called TDSS (time domain model for seafloor scattering), accurately treats the important point-source-point-receiver geometry for generally stratified fluid sediments—important because this is the geometry employed in many seabed scattering measurements. The computational cost associated with this model is very high and scales roughly with the product of mean source-receiver height above the basement to the fifth power and both bandwidth and wavenumber to the second power. Thus, modeling deep ocean scattering from a near sea surface source and receiver is prohibitive at frequencies above a few tens of hertz. A computational approach was developed based on Levin's method of oscillatory integration, which is orders of magnitude faster than standard numerical integration techniques and makes deep ocean seabed scattering computations practical up to many kilohertz. This approach was demonstrated to agree with the narrowband sonar equation in several simple environments in the limit of small bandwidths, but the TDSS model is expected to be valid for a much wider range of environments. [ABSTRACT FROM AUTHOR]

A vector sensor can provide measurements of ocean acoustic fields in terms of the acoustic pressure and three-dimensional particle velocity, providing potentially highly-informative data for applications such as geoacoustic inversion. This paper applies nonlinear Bayesian inversion to vector sensor data to estimate seabed geoacoustic properties and uncertainties in South China Sea. Linear-frequency-modulated source transmissions, recorded as acoustic pressure and vertical particle velocity, are processed to estimate the vertical phase gradient of acoustic pressure at multiple frequencies as the inversion data. An advantage of this type of data is that it can be modeled without knowledge of the source spectrum, allowing inversion with an unknown source and a single sensor. Geoacoustic inversion of phase-gradient data is carried out and compared to inversion of the vertical acoustic impedance, another type of vector-sensor data, independent of the source spectrum, which has been considered previously. Model selection for the optimal number of seabed sediment layers is carried out using Bayesian information criterion, and parameter estimates, uncertainties, and correlations are calculated using delayed-rejection adaptive Metropolis-Hastings sampling. Results indicate a three-layer seabed model (including the semi-infinite basement), with properties in agreement with independent measurements including a high-resolution seismic profile and surficial sediment type from a core. [ABSTRACT FROM AUTHOR]

Interferometry of ambient and shipping noise in the ocean provides a way to estimate physical parameters of the seafloor and the water column in an environmentally friendly manner without employing any controlled sound sources. With noise interferometry, two-point cross-correlation functions of noise serve as the probing signals and replace the Green's function measured in active acoustic remote sensing. The amount of environmental information that can be obtained with passive remote sensing and the robustness of the estimates of the seafloor parameters increase when contributions of individual normal modes are resolved in the noise cross-correlation function. Using the data obtained in the 2012 noise-interferometry experiment in the Straits of Florida, dispersion curves of the first four normal modes are obtained in this paper by application of the time-warping transform to noise cross correlations. The passively measured dispersion curves are inverted for unknown geoacoustic properties of the seabed. Resulting thickness of the sediment layer and sound speed are consistent with the geoacoustic models obtained earlier by other means. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) underwater sound field computations have been used for a few decades to understand sound propagation effects above sloped seabeds and in areas with strong 3D temperature and salinity variations. For an approximate simulation of effects in nature, the necessary 3D sound-speed field can be made from snapshots of temperature and salinity from an operational data-driven regional ocean model. However, these models invariably have resolution constraints and physics approximations that exclude features that can have strong effects on acoustics, example features being strong submesoscale fronts and nonhydrostatic nonlinear internal waves (NNIWs). Here, work to predict NNIW fields to improve 3D acoustic forecasts using an NNIW model nested in a tide-inclusive data-assimilating regional model is reported. The work was initiated under the Integrated Ocean Dynamics and Acoustics project. The project investigated ocean dynamical processes that affect important details of sound-propagation, with a focus on those with strong intermittency (high kurtosis) that are challenging to predict deterministically. Strong internal tides and NNIW are two such phenomena, with the former being precursors to NNIW, often feeding energy to them. Successful aspects of the modeling are reported along with weaknesses and unresolved issues identified in the course of the work. [ABSTRACT FROM AUTHOR]

A significant aspect of bottom-interaction in deep water acoustic propagation, from point sources to point receivers, is the diffraction (or scattering) of energy from discrete seafloor locations along repeatable, deterministic paths in three-dimensions. These bottom-diffracted surface-reflected (BDSR) paths were first identified on the North Pacific acoustic laboratory experiment in 2004 (NPAL04) for a diffractor located on the side of a small seamount. On the adjacent deep seafloor, ambient noise and propagation in the ocean sound channel were sufficiently quiet that the BDSRs were the dominant arrival. The ocean bottom seismometer augmentation in the North Pacific (OBSANP) experiment in June–July 2013 studied BDSRs at the NPAL04 site in more detail. BDSRs are most readily identified by the arrival time of pulses as a function of range to the receiver for a line of transmissions. The diffraction points for BDSRs occur on the relatively featureless deep seafloor as well as on the sides of small seamounts. Although the NPAL04 and OBSANP experiments had very different geometries the same diffractor location is consistent with observed arrivals in both experiments within the resolution of the analysis. On OBSANP the same location excites BDSRs for 77.5, 155, and 310 Hz transmissions. [ABSTRACT FROM AUTHOR]

Estuarine, riverine, and certain continental shelf environments experience significant temperature and salinity variability near the ocean bottom that can produce significant changes in how sound interacts with fine-grained sediments, presenting challenges in applications including shallow water sonar and bottom surveys. To begin to understand the effects of this variability on acoustic reflection, reflection measurements in the laboratory near 1 MHz were obtained from a water-clay interface while varying the salinity of the bottom water. At certain angles of incidence, salinity variations caused changes in bottom loss up to 15 dB and 180-degree phase shifts in the reflected signal, and induced changes in the reflectivity of the clay through the diffusion process, thereby leading to complicated, coupled interactions at the water-clay interface. By modeling the reflectivity of clay during molecular diffusion of salt, the diffusion coefficients were experimentally inferred and simulations at lower frequencies and longer timescales were performed. Derived characteristic length scales associated with the molecular diffusion of salt are compared with acoustic wavelengths to identify frequency regimes that are sensitive to salinity fluctuations. Results indicate that the dynamic nature of the bottom water can cause measurable and significant effects in reflectivity at and below frequencies applicable to sonar. [ABSTRACT FROM AUTHOR]

This Letter reports measurements of nonlinearity parameter B/A of water-saturated glass beads under uniaxial compression representative of the gravitational loading in seabed. The finite-amplitude method in conjunction with the multi-Gaussian beam model is used to determine B/A, in which the use of an accurate source function is found to be important in achieving the overall measurement accuracy. The estimated B/A is on the order of a hundred and decreases with increasing uniaxial compression up to 50 kPa, so that B/A could change as much as 20% over a depth of 5 m for a typical coarse sandy sediment. [ABSTRACT FROM AUTHOR]

A line array of 14 ocean bottom seismographs was deployed on the Exmouth Plateau northwest of the North West Cape in Western Australia in December 2014–January 2015. Acoustic data collected with this array were used to evaluate the corridor of the southbound migration of pygmy blue whales of the eastern Indian Ocean population. It is found that pygmy blue whales tended to travel southward much further away from the Western Australian coast, at distances of up to 400 km from shore, than that expected from data on their northbound migration. This is an important observation providing additional information on the migration pattern of pygmy blue whales, which is crucial for assessing their population and migration by passive acoustic means. [ABSTRACT FROM AUTHOR]

This paper presents single receiver geoacoustic inversion of a combustive sound source signal, recorded during the 2017 Seabed Characterization Experiment on the New England Mud Patch, in an area where water depth is around 70 m. There are two important features in this study. First, it is shown that high-order modes can be resolved and estimated using warping (up to mode number 18 over the frequency band 20–440 Hz). However, it is not possible to determine mode numbers from the data, so that classical inversion methods that require mode identification cannot be applied. To solve this issue, an inversion algorithm that jointly estimates geoacoustic properties and identifies mode number is proposed. It is successfully applied on a range-dependent track, and provides a reliable range-average estimation of geoacoustic properties of the mud layer, an important feature of the seabed on the experimental area. [ABSTRACT FROM AUTHOR]

A numerical approach for the treatment of irregular ocean bottoms within the framework of the standard parabolic equation is proposed. The present technique is based on the immersed interface method originally developed by LeVeque and Li [(1994). SIAM J. Numer. Anal. 31(4), 1019–1044]. The method conserves energy to high order accuracy and naturally handles generic range-dependent bathymetries, without requiring any additional specific numerical procedure. An illustration of its capabilities is provided by solving the well-known wedge problem. [ABSTRACT FROM AUTHOR]

The ocean acoustic noise floor (observed when the overhead wind is low, ships are distant, and marine life silent) has been measured on an array extending up 987 m from 5048 m depth in the eastern North Pacific, in what is one of only a few recent measurements of the vertical noise distribution near the seafloor in the deep ocean. The floor is roughly independent of depth for 1–6 Hz, and the slope (∼ f−7) is consistent with Longuet-Higgins radiation from oppositely-directed surface waves. Above 6 Hz, the acoustic floor increases with frequency due to distant shipping before falling as ∼ f−2 from 40 to 800 Hz. The noise floor just above the seafloor is only about 5 dB greater than during the 1975 CHURCH OPAL experiment (50–200 Hz), even though these measurements are not subject to the same bathymetric blockage. The floor increases up the array by roughly 15 dB for 40–500 Hz. Immediately above the seafloor, the acoustic energy is concentrated in a narrow, horizontal beam that narrows as f−1 and has a beam width at 75 Hz that is less than the array resolution. The power in the beam falls more steeply with frequency than the omnidirectional spectrum. [ABSTRACT FROM AUTHOR]

A striation-based method with a vertical line array is proposed for source depth estimation. Broadband striation structures of direct and surface-reflected arrivals after propagating to receivers near the ocean bottom are applied. A tracking algorithm for the striation structures is proposed based on the extended Kalman filter. A cost function for source depth estimation is presented by matching the traces of the measured striations with a library of model-based traces under different source depths. The method is demonstrated on array data collected during an acoustic research experiment in the South China Sea in 2016. [ABSTRACT FROM AUTHOR]

Sound produced by marine pile driving activities poses a possible risk to marine life. The assessment and mitigation of this risk requires a precise prediction of the expected levels. An analytical approach to estimate the radiated sound exposure levels is presented, based on the axial symmetry of the problem, resulting in damped cylindrical spreading. The approach is verified against numerical results from the recently held COMPILE benchmark workshop and validated with data from three different wind farm construction sites in the North Sea. In addition, found to yield more accurate estimates of the sound exposure level than an empirical decay formula sometimes used to evaluate the impact of marine pile driving. [ABSTRACT FROM AUTHOR]

Bottom scattering is important for a number of underwater applications: it is a source of noise in target detection and a source of information for sediment classification and geoacoustic inversion. While current models can predict the effective interface scattering strength for layered sediments, these models cannot directly compute the ensemble averaged mean-square pressure. A model for bottom scattering due to a point source is introduced which provides a full-wave solution for mean-square scattered pressure as a function of time under first-order perturbation theory. Examples of backscatter time series from various types of seafloors will be shown, and the advantages and limitations of this model will be discussed. [ABSTRACT FROM AUTHOR]

The frequency bandwidth of the sound from a light helicopter, such as a Robinson R44, extends from about 13 Hz to 2.5 kHz. As such, the R44 has potential as a low-frequency sound source in underwater acoustics applications. To explore this idea, an experiment was conducted in shallow water off the coast of southern California in which a horizontal line of hydrophones detected the sound of an R44 hovering in an end-fire position relative to the array. Some of the helicopter sound interacted with seabed to excite the head wave in the water column. A theoretical analysis of the sound field in the water column generated by a stationary airborne source leads to an expression for the two-point horizontal coherence function of the head wave, which, apart from frequency, depends only on the sensor separation and the sediment sound speed. By matching the zero crossings of the measured and theoretical horizontal coherence functions, the sound speed in the sediment was recovered and found to take a value of 1682.42 ± 616.20 m/s. This is consistent with the sediment type at the experiment site, which is known from a previous survey to be a fine to veryfine sand. [ABSTRACT FROM AUTHOR]