Estimation of average under-ice reflection amplitudes and phases using matched-field processing

Livingston, Ellen S.; Diachok, Orest

doi:10.1121/1.398569

Cited by 26 publications

(9 citation statements)

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“…Livingston and Diachok [64] applied MFT for the purpose of investigating under-ice reflectivity to the same data set from FRAl\1 IV that Yang [105] used for the early MFP demonstrations. Recently, Miller and Schmidt [68] applied full wave solutions to the elastic wave equation [83] as replicas to perform MFT to determine the bulk properties of Arctic ice.…”

Section: Matched Field Tomographymentioning

confidence: 99%

Matched Field Processing in Ocean Acoustics

Baggeroer

Kuperman

1993

Acoustic Signal Processing for Ocean Exploration

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ABSTRACT. Matched field processing (MFP) is a generalized beam forming method which uses the spatial complexities of acoustic fields in an ocean wavegnide to localize sources in range, depth and azimuth or to infer parameters of the waveguide it.self. It has experimentally localized sources with accuracies exceeding the Rayleigh limit for depth and the Fresnel limit for range by two orders of magnitude. MFP exploits the coherence of the modefmultipath structure and it is especially effective at low frequencies where the ocean supports coherent propagation over very loug ranges. This contrasts with plane wave based models which are degraded by modal and lUultipath phenomena and are generally ineffective when waveguide phenomena are important. MFP is a spatial matched fLlter where the correlation signal, or replica, is determined by the Green's function of the waveguide. It can have either conventional or adaptive formulations and it has been implemented with an a.-;sortment of both narrowband and wideband signal models. All involve some form of correlation betwcen the replicas deri ved from the wave equation and the data measured at an array of sensors. Since the replica gcnerally has a complicated dependence upon the source location and environmental parameters, the wave eqnation mllst be solved over this parameter space. One can view MFP as an inverse problem where one attempts to invert for these dependencies over the parameter space of the source and the environment. There is cUlTently a large literature discussing many theoretical aspects of MFP and this is supported by numerous simulations; several experiments acquiring data for MFP now have been conducted in several ocean environments and these have demonstrated both its capabilities and some of its limitations. Consequently, there is a modest understanding of both the theory and the experimental capabilities of MFP. This article provides an oVl!fvicw of both.

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Section: Matched Field Tomographymentioning

confidence: 99%

Matched Field Processing in Ocean Acoustics

Baggeroer

Kuperman

1993

Acoustic Signal Processing for Ocean Exploration

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“…Although MFP was originally used for source localization, it was subsequently applied to estimation of environmental parameters as well. [2][3][4][5][6][7][8] MFP, when applied for the estimation of environmental parameters, is often referred to as matched-field inversion (MFI).…”

Section: Introductionmentioning

confidence: 99%

Sound speed estimation and source localization with linearization and particle filtering

Lin

Michalopoulou

2014

The Journal of the Acoustical Society of America

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A method is developed for the estimation of source location and sound speed in the water column relying on linearization. The Jacobian matrix, necessary for the proposed linearization approach, includes derivatives with respect to empirical orthogonal function coefficients instead of sound speed directly. First, the inversion technique is tested on synthetic arrival times, using Gaussian distributions for the errors in the considered arrival times. The approach is efficient, requiring a few iterations, and produces accurate results. Probability densities of the estimates are calculated for different levels of noise in the arrival times. Subsequently, particle filtering is employed for the estimation of arrival times from signals recorded during the Shallow Water 06 experiment. It has been shown in the past that particle filtering can be employed for the successful estimation of multipath arrival times from short-range data and, consequently, in geometry, bathymetry, and sound speed inversion. Here probability density functions of arrival times computed via particle filtering are propagated backward through the proposed inversion process. Inversion estimates are consistent with values reported in the literature for the same quantities. Last it is shown that results are consistent with estimates resulting from fast simulated annealing applied to the same data.

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“…Inversion is performed by identifying those values of the model parameters that maximize or minimize a measure (depending on its nature) between replica and true acoustic fields: A misfit function is often minimized between acoustic field and replicas. MFP was originally used for source localization and was later adapted and applied to estimation of environmental parameters [2]. MFP applied to the inverse problem of estimating environmental parameters is typically referred to as matched-field inversion (MFI).…”

Section: Introductionmentioning

confidence: 99%

A Direct Method for the Estimation of Sediment Sound Speed With a Horizontal Array in Shallow Water

Lin

Michalopoulou

2016

IEEE J. Oceanic Eng.

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In this paper, a fast approach for estimating sediment sound speed in a shallow-water environment is developed. Under certain assumptions, this algorithm recovers the seabed sound-speed profile using pressure field measurements at low frequencies. The geometry of the problem involves measuring the pressure at horizontally placed hydrophones in the water column. The Deift-Trubowitz integral equation is then solved. This work introduces two methods for this task. The first is a modified Born approximation that builds upon a standard first-order approximation; the second is based on interpolating the integrand. It is shown with synthetic data that these methods work well with successful sound-speed estimation and identification of sharp discontinuities in sound speed. Although the methods are stable and effective with noise-free data, problems arise when noise contaminates the acoustic field. Regularization approaches, reducing the disruptive effect of singular points and smoothing a measured reflection coefficient, are developed to remedy this problem, leading to improved results in noisy environments. In addition to providing soundspeed estimates, the method also computes sediment thickness. This feature is of particular interest, since it makes the method suitable as a preprocessing step providing useful information to other inversion methods. Sensitivity analyses demonstrate that some assumptions required for the approach implementation are not restrictive.Index Terms-Direct methods, geoacoustic inversion, sediment sound speed.

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Estimation of average under-ice reflection amplitudes and phases using matched-field processing

Cited by 26 publications

References 0 publications

Matched Field Processing in Ocean Acoustics

Matched Field Processing in Ocean Acoustics

Sound speed estimation and source localization with linearization and particle filtering

A Direct Method for the Estimation of Sediment Sound Speed With a Horizontal Array in Shallow Water

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