Phase stability of convergence zone propagation at mid-frequency.

Mid-frequency transmissions (1.5 to 7.5 kHz) from a towed source to a drifting array one convergence zone away demonstrate smoothly varying phase.

Deep sediment heterogeneity inferred using very low-frequency features from merchant shipsa).

The very low-frequency noise from merchant ships provides a good broadband sound source to study the deep layers of the seabed. The nested striations that characterize ship time-frequency spectrograms contain unique acoustic features corresponding to where the waveguide invariant β becomes infinite. In this dataset, these features occur at frequencies between 20 and 80 Hz, where pairs of modal group velocities become equal.

Mid-frequency acoustic tracking of breaking waves.

Large surface wave breaking events in deep water are acoustically detectable by beamforming at 5-6 kHz with a mid-frequency planar array located 130 m below the surface. Due to the array's depth and modest 1 m horizontal aperture, wave breaking events cannot be tracked accurately by beamforming alone. Their trajectories are estimated instead by splitting the array into sub-arrays, beamforming each sub-array toward the source, and computing the temporal cross-correlation of the sub-array beams.

Inference of source signatures of merchant ships in shallow ocean environmentsa).

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.

Mid-frequency acoustic localization of breaking waves.

During an experiment in deep water off the coast of Southern California, wind speeds ranged from 10 to 15 m/s and wind forcing produced large breaking waves. A mid-frequency vertical planar hydrophone array recorded underwater ambient noise while an airplane equipped with a high-resolution video camera captured images of the sea surface above the array. Beams of ambient noise between 5 and 6 kHz were projected onto the sea surface and synchronized in space and time with the aerial images.

Active intensity vortex and stagnation point singularities in a shallow underwater waveguide.

Vector acoustic properties of a narrowband acoustic field are observed as a function of range from a source towed in waters of depth 77 m on the New England Mud Patch. At the source frequency (43 Hz), the waveguide supported three trapped modes, with mode 2 weakly excited owing to the towed source depth. The receiving sensor was positioned 1.

Observations and simulations of caustic formation due to oceanographic fine structure.

An at-sea experiment in deep water was conducted to explore the impact of small-scale sound-speed variability on mid-frequency (1-10 kHz) acoustic propagation. Short-range (1-5 km) acoustic transmissions were sent through the upper ocean (0-200 m) while oceanographic instruments simultaneously measured the ocean environment within 2 km of the single upper turning points of the acoustic transmissions. During these transmissions, acoustic receptions over a 7.

Acoustic ducting by shelf water streamers at the New England shelfbreak.

Greater sound speed variability has been observed at the New England shelfbreak due to a greater influence from the Gulf Stream with increased meander amplitudes and frequency of Warm Core Ring (WCR) generation. Consequently, underwater sound propagation in the area also becomes more variable. This paper presents field observations of an acoustic near-surface ducting condition induced by shelf water streamers that are related to WCRs.

Moving source ocean acoustic tomography with uncertainty quantification using controlled source-tow observations.

Ocean sound speed and its uncertainty are estimated using travel-time tomography at ranges up to 2 km using a moving source in ∼600 m water depth. The experiment included two 32-element vertical line arrays deployed about 1 km apart and a towed source at ∼10 m depth transmitting a linear frequency modulated waveform. The inversion accounts for uncertainties in the positions and velocities of the source and receivers in addition to the background sound speed state.

A performance comparison between m-sequences and linear frequency-modulated sweeps for the estimation of travel-time with a moving source.

This manuscript discusses the utility of maximal period linear binary pseudorandom sequences [also referred to as m-sequences or maximum length sequences (MLSs)] and linear frequency-modulated (LFM) sweeps for the purpose of measuring travel-time in ocean-acoustic experiments involving moving sources. Signal design and waveform response to unknown Doppler (waveform dilation or scale factor) are reviewed. For this two-parameter estimation problem, the well-known wide-band ambiguity function indicates, and moving-source observations corroborate, a significant performance benefit from using MLS over LFM waveforms of similar time duration and bandwidth.

Seabed classification from merchant ship-radiated noise using a physics-based ensemble of deep learning algorithms.

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%.

Seabed type and source parameters predictions using ship spectrograms in convolutional neural networks.

Broadband spectrograms from surface ships are employed in convolutional neural networks (CNNs) to predict the seabed type, ship speed, and closest point of approach (CPA) range. Three CNN architectures of differing size and depth are trained on different representations of the spectrograms. Multitask learning is employed; the seabed type prediction comes from classification, and the ship speed and CPA range are estimated via regression.

Reverberation due to a moving, narrowband source in an ocean waveguide.

In this paper, a model for the bistatic reverberation associated with seafloor scattering of sound from a moving, narrowband source in an ocean waveguide is developed. Studies of the Doppler effect for moving sources in waveguides have typically focused on the forward propagating field where the Doppler shift leads to a splitting or broadening of the received spectrum. In contrast, the contributions to the scattered field come from all directions and as a consequence the spectrum of the received energy is spread across the entire range of Doppler-shifted frequencies possible for the speed of the source.

Estimating relative channel impulse responses from ships of opportunity in a shallow water environment.

The uncertainty of estimating relative channel impulse responses (CIRs) obtained using the radiated signature from a ship of opportunity is investigated. The ship observations were taken during a 1.4 km (11 min) transect in a shallow water environment during the Noise Correlation 2009 (NC09) experiment.

A double-difference method for high-resolution acoustic tracking using a deep-water vertical array.

Ray-tracing is typically used to estimate the depth and range of an acoustic source in refractive deep-water environments by exploiting multipath information on a vertical array. However, mismatched array inclination and uncertain environmental features can produce imprecise trajectories when ray-tracing sequences of individual acoustic events. "Double-difference" methods have previously been developed to determine fine-scale relative locations of earthquakes along a fault [Waldhauser and Ellsworth (2000).

Multi-frequency sparse Bayesian learning for robust matched field processing.

The multi-snapshot, multi-frequency sparse Bayesian learning (SBL) processor is derived and its performance compared to the Bartlett, minimum variance distortionless response, and white noise constraint processors for the matched field processing application. The two-source model and data scenario of interest includes realistic mismatch implemented in the form of array tilt and data snapshots not exactly corresponding to the range-depth grid of the replica vectors. Results demonstrate that SBL behaves similar to an adaptive processor when localizing a weaker source in the presence of a stronger source, is robust to mismatch, and exhibits improved localization performance when compared to the other processors.

Multiple-array passive acoustic source localization in shallow water.

This paper considers concurrent matched-field processing of data from multiple, spatially-separated acoustic arrays with application to towed-source data received on two bottom-moored horizontal line arrays from the SWellEx-96 shallow water experiment. Matched-field processors are derived for multiple arrays and multiple-snapshot data using maximum-likelihood estimates for unknown complex-valued source strengths and unknown error variances. Starting from a coherent processor where phase and amplitude is known between all arrays, likelihood expressions are derived for various assumptions on relative source spectral information (amplitude and phase at different frequencies) between arrays and from snapshot to snapshot.

Adaptive and compressive matched field processing.

Matched field processing is a generalized beamforming method that matches received array data to a dictionary of replica vectors in order to locate one or more sources. Its solution set is sparse since there are considerably fewer sources than replicas. Using compressive sensing (CS) implemented using basis pursuit, the matched field problem is reformulated as an underdetermined, convex optimization problem.

Change-point detection for recursive Bayesian geoacoustic inversions.

In order to carry out geoacoustic inversion in low signal-to-noise ratio (SNR) conditions, extended duration observations coupled with source and/or receiver motion may be necessary. As a result, change in the underlying model parameters due to time or space is anticipated. In this paper, an inversion method is proposed for cases when the model parameters change abruptly or slowly.

Recursive Bayesian synthetic aperture geoacoustic inversion in the presence of motion dynamics.

A low signal to noise ratio (SNR), single source/receiver, broadband, frequency-coherent matched-field inversion procedure recently has been proposed. It exploits coherently repeated transmissions to improve estimation of the geoacoustic parameters. The long observation time improves the SNR and creates a synthetic aperture due to relative source-receiver motion.

Compressive geoacoustic inversion using ambient noise.

Surface generated ambient noise can be used to infer sediment properties. Here, a passive geoacoustic inversion method that uses noise recorded by a drifting vertical array is adopted. The array is steered using beamforming to compute the noise arriving at the array from various directions.

Spatial filtering in ambient noise interferometry.

Theoretically, the empirical Green's function between a pair of receivers can be extracted from the cross correlation of the received diffuse noise. The diffuse noise condition rarely is met in the ocean and directional sources may bias the Green's function. Here matrix-based spatial filters are used for removing unwanted contributions in the cross correlations.

Measuring the effect of ambient noise directionality and split-beam processing on the convergence of the cross-correlation function.

Measurements of ambient noise have been used to infer information about the ocean acoustic environment. In recent years the correlation of ambient noise has been shown to give estimates of the travel time of acoustic paths between the sensors recording the noise. A number of issues affect the results of the noise correlation.