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Stan E Dosso

Publications and source records attributed to Stan E Dosso.

8 recordsLinked to original sources
PubMed2006

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). However, the latter assumption is often not valid due to theory errors, and can lead to reduced accuracy for geoacoustic parameter estimates and underestimation of parameter uncertainties. This paper examines the effects of data error (residual) covariance in matched-field geoacoustic inversion. An inversion approach is developed based on a nonparametric method of estimating the full covariance matrix (including off-diagonal terms) from the data residuals and explicitly including this covariance in the misfit function. Qualitative and quantitative statistical tests for Gaussianity and for correlations in complex residuals are considered to validate the inversion results. The approach is illustrated for Bayesian geoacoustic inversion of broadband, vertical-array acoustic data measured in the Mediterranean Sea.

Journal Article↗
PubMed2005

Remote sensing of sediment density and velocity gradients in the transition layer.

The geoacoustic properties of marine sediments, e.g., bulk density and compressional velocity, commonly exhibit large variations in depth near the water-sediment interface. This layer, termed the transition layer, is typically of 0(10(-1)-10(0)) m in thickness. Depth variations within the transition layer may have important implications for understanding and modeling acoustic interaction with the seabed, including propagation and reverberation. In addition, the variations may contain significant clues about the underlying depositional or erosional processes. Characteristics of the transition layer can be measured directly (e.g., coring) or remotely. Remote measurements have the advantage of sampling without disturbing the sediment properties; they also have the potential to be orders of magnitude faster and less expensive than direct methods. It is shown that broadband seabed reflection data can be exploited to remotely obtain the depth dependent density and velocity profiles in the transition layer to high accuracy. A Bayesian inversion approach, which accounts for correlated data errors, provides estimates and uncertainties for the geoacoustic properties. These properties agree with direct (i.e., core) measurements within the uncertainty estimates.

Journal Article↗
PubMed2002

Quantifying uncertainty in geoacoustic inversion. I. A fast Gibbs sampler approach.

This paper develops a new approach to estimating seabed geoacoustic properties and their uncertainties based on a Bayesian formulation of matched-field inversion. In Bayesian inversion, the solution is characterized by its posterior probability density (PPD), which combines prior information about the model with information from an observed data set. To interpret the multi-dimensional PPD requires calculation of its moments, such as the mean, covariance, and marginal distributions, which provide parameter estimates and uncertainties. Computation of these moments involves estimating multi-dimensional integrals of the PPD, which is typically carried out using a sampling procedure. Important goals for an effective Bayesian algorithm are to obtain efficient, unbiased sampling of these moments, and to verify convergence of the sample. This is accomplished here using a Gibbs sampler (GS) approach based on the Metropolis algorithm, which also forms the basis for simulated annealing (SA). Although GS can be computationally slow in its basic form, just as modifications to SA have produced much faster optimization algorithms, the GS is modified here to produce an efficient algorithm referred to as the fast Gibbs sampler (FGS). An automated convergence criterion is employed based on monitoring the difference between two independent FGS samples collected in parallel. Comparison of FGS, GS, and Monte Carlo integration for noisy synthetic benchmark test cases indicates that FGS provides rigorous estimates of PPD moments while requiring orders of magnitude less computation time.

Acoustics↗
PubMed2002

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. Invoking the simplifying assumption of independent, identically distributed Gaussian errors allows a maximum-likelihood estimate of the data variance and leads to a practical inversion algorithm. However, it is necessary to validate these assumptions, i.e., to verify that the parameter uncertainties obtained represent meaningful estimates. To this end, FGS is applied to a geoacoustic experiment carried out at a site off the west coast of Italy where previous acoustic and geophysical studies have been performed. The parameter uncertainties estimated via FGS are validated by comparison with: (i) the variability in the results of inverting multiple independent data sets collected during the experiment; (ii) the results of FGS inversion of synthetic test cases designed to simulate the experiment and data errors; and (iii) the available geophysical ground truth. Comparisons are carried out for a number of different source bandwidths, ranges, and levels of prior information, and indicate that FGS provides reliable and stable uncertainty estimates for the geoacoustic inverse problem.

Acoustics↗
PubMed2002

Acoustic tracking of a freely drifting sonobuoy field.

This paper develops an acoustic inversion algorithm to track a field of freely drifting sonobuoys using travel-time measurements from a series of nonsimultaneous impulsive sources deployed around the field. In this scenario, the time interval between sources can be sufficiently long that significant independent movement of the individual sonobuoys occurs. In addition, the source transmission instants are unknown, and the source positions and initial sonobuoy positions are known only approximately. The formulation developed here solves for the track of each sonobuoy (parametrized by the sonobuoy positions at the time of each source transmission), allowing arbitrary, independent sonobuoy motion between transmissions, as well as for the source positions and transmission instants. This leads to a strongly underdetermined inverse problem. However, regularized inversion provides meaningful solutions by incorporating a priori information consisting of prior estimates (with uncertainties) for the source positions and initial sonobuoy positions, and a physical model for preferred sonobuoy motion. Several models for sonobuoy motion are evaluated, with the best results obtained by minimizing the second spatial derivative of the tracks to obtain the minimum-curvature or smoothest track, subject to fitting the acoustic data to a statistically appropriate level.

Journal Article↗
PubMed2002

Effects of incoherent and coherent source spectral information in geoacoustic inversion.

This paper examines the effect on matched-field geoacoustic inversion of including source spectral information, as can be available in controlled-source acoustic surveys. Source information can consist of relative or absolute knowledge of the source amplitude and/or phase spectra, and can allow frequency-coherent processing of spatial acoustic-field data. A number of multi-frequency acoustic processors, appropriate for specific types of source information, are defined based on the likelihood function for complex acoustic-field data with Gaussian noise. The information content of the various processors is quantified in terms of marginal probability distributions and highest-probability density intervals for the unknown geoacoustic and geometric parameters, which define the accuracy expected in inversion. Marginal distributions are estimated using a fast Gibbs sampler approach to Bayesian inversion, which provides an efficient, unbiased sampling of the multi-dimensional posterior probability density. The analysis is illustrated for incoherent and coherent processors corresponding to several types of source knowledge ranging from complete information to no information, and the results are considered as a function of the spatial and frequency sampling of the acoustic fields.

Acoustics↗
PubMed2002

Source bearing estimation in the Arctic Ocean using ice-mounted geophones.

This paper investigates the use of geophones mounted on the surface of Arctic sea ice for estimating the bearing to acoustic sources in the water column. The approach is based on measuring ice seismic waves for which the direction of particle motion is oriented radially outward from the source. However, the analysis is complicated by the fact that sea ice supports several types of seismic waves, producing complex particle motion that includes significant nonradial components. To suppress seismic waves with transverse particle motion, seismic polarization filters are applied in conjunction with a straightforward rotational analysis (computation of particle-motion power as a function of angle). The polarization filters require three-dimensional (3D) measurements of particle motion, and apply theoretical phase relationships between vertical and horizontal components for the various waves types. In addition, the 180 degrees ambiguity inherent in the rotational analysis can be resolved with 3D measurements by considering particle motion in the vertical-radial plane. Arctic field trials were carried out involving two components. First, a hammer source was used to selectively excite the various ice seismic waves to investigate their propagation properties and relative importance in bearing estimation. Second, impulsive acoustic sources were deployed in the water column at a variety of bearings and ranges from 200-1000 m. For frequencies up to 250 Hz, source bearings are typically estimated to within an average absolute error of approximately 100.

Journal Article↗