Frequency based noise coherence-function extension and application to passive bottom-loss estimation.

Accurate modeling of acoustic propagation in the ocean waveguide is important to SONAR-performance prediction. Particularly in shallow waters, a crucial contribution to the total transmission loss is the bottom refection loss, which can be estimated passively by beamforming the natural surface-noise acoustic field recorded by a vertical line array of hydrophones. However, the performance in this task of arrays below 2 m of length is problematic for frequencies below 10 kHz It is shown in this paper that, when the data are free of interference from sources other than wind and wave surface noise, data from a shorter array can be used to approximate the coherence function of a longer array.

Geoacoustic inversion of ship radiated noise in shallow water using data from a single hydrophone.

The Centre for Maritime Research and Experimentation conducted a geoacoustic inverse experiment in the Mediterranean Sea in the summer of 2012. Among the objectives was to employ an autonomous underwater vehicle to collect acoustic data to invert for properties of the seafloor. Inversion results for the compression wave speed in the bottom and the source spectrum of the R/V Alliance during a close approach to the bottom moored vehicle are presented.

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.

Synthetic array processing of ocean ambient noise for higher resolution seabed bottom loss estimation.

Predicting transmission loss in the ocean often strongly depends on the bottom loss. Bottom loss can be estimated using ocean noise and vertical array beam-forming [Harrison and Simons, J. Acoust.

Resolving meso-scale seabed variability using reflection measurements from an autonomous underwater vehicle.

Seabed geoacoustic variability is driven by geological processes that occur over a wide spectrum of space-time scales. While the acoustics community has some understanding of horizontal fine-scale geoacoustic variability, less than O(10(0)) m, and large-scale variability, greater than O(10(3)) m, there is a paucity of data resolving the geoacoustic meso-scale O(10(0)-10(3)) m. Measurements of the meso-scale along an ostensibly "benign" portion of the outer shelf reveal three classes of variability.

Bayesian source tracking via focalization and marginalization in an uncertain Mediterranean Sea environment.

This paper applies Bayesian source tracking in an uncertain environment to Mediterranean Sea data, and investigates the resulting tracks and track uncertainties as a function of data information content (number of data time-segments, number of frequencies, and signal-to-noise ratio) and of prior information (environmental uncertainties and source-velocity constraints). To track low-level sources, acoustic data recorded for multiple time segments (corresponding to multiple source positions along the track) are inverted simultaneously. Environmental uncertainty is addressed by including unknown water-column and seabed properties as nuisance parameters in an augmented inversion.

Bayesian inversion of reverberation and propagation data for geoacoustic and scattering parameters.

This paper applies nonlinear Bayesian inference theory to quantify the information content of reverberation and short-range propagation data, both individually and in joint inversion, to resolve seabed geoacoustic and scattering properties. The inversion of reverberation data alone is shown to poorly resolve seabed properties because of strong multi-dimensional correlations between parameters. Inversion of propagation data alone is limited by different correlations, but better constrains the geoacoustic parameters.

Geoacoustic inversion using multipath pulse shape.

Experimental data, measured in a shallow water region of the Mediterranean Sea, are used to show that the variation of received intensity with time is well described by existing expressions [Harrison and Nielsen, J. Acoust. Soc.

Multipath pulse shapes in shallow water: theory and simulation.

In shallow water propagation the steeper ray angles are weakened most by boundary losses. Regarding the sound intensity as a continuous function of angle it can be converted into a function of travel time to reveal the multipath pulse shape received from a remote source (one-way path) or a target (two-way path). The closed-form isovelocity pulse shape is extended here to the case of upward or downward refraction.

Data error covariance in matched-field geoacoustic inversion.

Many approaches to geoacoustic inversion are based implicitly on the assumptions that data errors are Gaussian-distributed and spatially uncorrelated (i.e., have a diagonal covariance matrix).

Range-dependent seabed characterization by inversion of acoustic data from a towed receiver array.

The MAPEX2000 experiments were conducted in the Mediterranean Sea in March, 2000 to determine seabed properties using a towed acoustic source and receiver array. Towed systems are advantageous because they are easy to deploy from a ship and the moving platform offers the possibility for estimating spatially variable (range-dependent) seabed properties. In this paper, seabed parameters are determined using a matched-field geoacoustic inversion approach with measured, towed array data.

Quantifying uncertainty in geoacoustic inversion. II. Application to broadband, shallow-water data.

This paper applies the new method of fast Gibbs sampling (FGS) to estimate the uncertainties of seabed geoacoustic parameters in a broadband, shallow-water acoustic survey, with the goal of interpreting the survey results and validating the method for experimental data. FGS applies a Bayesian approach to geoacoustic inversion based on sampling the posterior probability density to estimate marginal probability distributions and parameter covariances. This requires knowledge of the statistical distribution of the data errors, including both measurement and theory errors, which is generally not available.