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Environmental inversion using high-resolution matched-field processinga)
a)Portions of this work were presented at the European Conference on Underwater Acoustics on June 2006, Carvoeiro, Portugal.
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Image of FIG. 1.
FIG. 1.

(Color online) The behavior of the broadband processors for the coherent case assuming an unknown signal matrix.

Image of FIG. 2.
FIG. 2.

RMSE as a function of the number of snapshots for the three processors and the coherent model Cramer-Rao lower bound under comparison: (a) With known signal matrix and (b) with unknown signal matrix and signal subspace dimension.

Image of FIG. 3.
FIG. 3.

Eigenspectra for finite number of signal observations: (a) Comparison of two eigen-spectra using (gray) and black; (b) average eigenspectrum for a varying number of signal realizations; and (c) average order estimation for a varying number of signal realizations.

Image of FIG. 4.
FIG. 4.

A posteriori probability distributions for each parameter based on the last generation of 50 independent populations. Each column corresponds to processors entering the comparison. The gray asterisks indicate the correct parameter value.

Image of FIG. 5.
FIG. 5.

(Color online) The Maritime Rapid Environmental Assessment 2003 (MREA’03) experimental area: (a) Black circles indicate the sampling grid setup for the CTD measurements used in this study, and the dashed white box limits the area where the acoustic experiment of 21 June took place and (b) GPS estimated source ship navigation (white solid curve) and AOB drift (white dashed curve) during the deployment of 21 June.

Image of FIG. 6.
FIG. 6.

Source range (a) and depth (b) measured during the deployment of 21 June. The curves are broken indicating change of the emitted wave form. A1, A2, and A1double denote the wave forms emitted in each interval.

Image of FIG. 7.
FIG. 7.

Example of an A1 chirp received on the AOB.

Image of FIG. 8.
FIG. 8.

CTD-based data used for temperature estimation taken during 16, 17, and 19 June Temperature profiles with mean profile in solid black (left) and representative empirical orthogonal functions (EOF) computed from the temperature profiles (right).

Image of FIG. 9.
FIG. 9.

Baseline model for the MREA’03 sea trial. All parameters except water depth are range independent.

Image of FIG. 10.
FIG. 10.

Source localization obtained with the MUSIC processor. Source range (a) and source depth (b). True location is given by the black curve in the background. The gray curves with circles are the source localization results. The black asterisks indicate the successful localizations.

Image of FIG. 11.
FIG. 11.

Model parameter estimates obtained via acoustic data inversion using the BB MUSIC processor. Water column [(a) and (b)]; sediment [(c)–(g)]; and subbottom [(h)–(j)]. The black asterisks indicate model estimates allowing for successful source localization in the validation step.

Image of FIG. 12.
FIG. 12.

A posteriori probability distributions for the seafloor parameters based on the last generation of the GA. Only inversions validated by means of source localization during the A2 period are considered. The gray asterisk indicates the baseline value of the parameter.


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Peak-to-surface average ratio obtained for the different processors.

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Signal emission schedule on 21 June. The times are in GMT.

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GA settings for environmental inversion.

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Rates of successful localization (%) for the different processors and different wave forms.

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Baseline seafloor parameters, parameter MAP estimates on 43 GA populations, and a reliability measure.


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Environmental inversion using high-resolution matched-field processinga)