Techniques for modeling ocean soundscapes: Detailed description for wind contributionsa).

Wind over the ocean creates breaking waves that generate air-filled bubbles, which radiate underwater sound. This wind-generated sound is a significant component of the ocean soundscape, and models are essential for understanding and predicting its impact. Models for predicting sound pressure level (SPL) from wind have been studied for many years.

Verifying models of the underwater soundscape from wind and ships with benchmark scenariosa).

Models of the underwater acoustic soundscape are important for evaluating the effects of human generated sounds on marine life. The performance of models can be validated against measurements or verified against each other for consistency. A verification workshop was held to compare models that predict the soundscape from wind and vessels and estimate detection ranges for a submerged target.

On the limits of distinguishing seabed types via ambient acoustic sound.

This article presents a theoretical analysis of optimally distinguishing among environmental parameters from ocean ambient sound. Recent approaches to this problem either focus on parameter estimation or attempt to classify the environment into one of many known types through machine learning. This classification problem is framed as one of hypothesis testing on the received ambient sound snapshots.

Optimal environmental estimation with ocean ambient noise.

This article presents an asymptotically optimal technique for estimating environmental parameters from ocean ambient noise. Noise from wind and breaking waves propagates through the water column and reflects off the bottom over a wide range of angles and frequencies and, in doing so, imparts information about the environment to the noise covariance matrix for a receiver array. Most environmental estimation techniques focus on spatial filtering methods aimed at recovering the vertical noise directionality.

Environmental information content of ocean ambient noise.

In recent years, methods have been developed to estimate a variety of environmental parameters based on measurements of the ocean ambient noise. For example, noise has been used to estimate water depth using the passive fathometer technique and bottom loss estimated and used to invert for seabed parameters. There is also information in the noise about the water column sound speed, volume attenuation, and the sea-state.

An analysis of beamforming algorithms for passive bottom reflection-loss estimation.

This study provides an argument cautioning against the use of adaptive-beamforming (ABF) techniques in conjunction with a known method for estimating the bottom reflection loss from natural marine ambient noise. This application of ABF has been investigated in the past with rather inconsistent results. Furthermore, no formal proof that ABF algorithms do indeed provide an estimate of the bottom reflection loss is available.

Head wave correlations in ambient noise.

Ambient ocean noise is processed with a vertical line array to reveal coherent time-separated arrivals suggesting the presence of head wave multipath propagation. Head waves, which are critically propagating water waves created by seabed waves traveling parallel to the water-sediment interface, can propagate faster than water-only waves. Such eigenrays are much weaker than water-only eigenrays, and are often completely overshadowed by them.

A two-hydrophone range and bearing localization algorithm with performance analysis.

An automated, passive algorithm for detecting and localizing small boats using two hydrophones mounted on the seabed is outlined. This extends previous work by Gebbie et al. [(2013).

Passive localization of noise-producing targets using a compact volumetric array.

A technique is presented for passively localizing multiple noise-producing targets by cross-correlating the elevation beams of a compact volumetric array on separate bearings. A target's multipath structure inherently contains information about its range; however, unknown, random noise waveforms make time separation of individual arrivals difficult. Ocean ambient noise has previously been used to measure multipath delays to the seabed by cross-correlating the beams of a vertical line array [Siderius, Song, Gerstoft, Hodgkiss, Hursky, and Harrison, J.

Localization of a noisy broadband surface target using time differences of multipath arrivals.

Previous studies [Tiemann et al., J. Acoust.

Aspect-dependent radiated noise analysis of an underway autonomous underwater vehicle.

This paper presents an analysis of the acoustic emissions emitted by an underway REMUS-100 autonomous underwater vehicle (AUV) that were obtained near Honolulu Harbor, HI using a fixed, bottom-mounted horizontal line array (HLA). Spectral analysis, beamforming, and cross-correlation facilitate identification of independent sources of noise originating from the AUV. Fusion of navigational records from the AUV with acoustic data from the HLA allows for an aspect-dependent presentation of calculated source levels of the strongest propulsion tone.