Geoacoustic Inversions of Horizontal and Vertical Line Array Acoustic Data From a Surface Ship Source of Opportunity

Stotts, Steven A.; Koch, Robert; Joshi, Sumedh M.; Nguyen, Vian T.; Ferreri, V.W.; Knobles, David P.

doi:10.1109/joe.2009.2032256

Cited by 21 publications

(8 citation statements)

References 29 publications

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“…The idea is to select frequencies that have clearly identifiable modal interference patterns with about 5 maxima and minima over a time/range interval. 23 …”

Section: Stepmentioning

confidence: 99%

Maximum entropy inference of seabed attenuation parameters using ship radiated broadband noise

Knobles

2015

The Journal of the Acoustical Society of America

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The received acoustic field generated by a single passage of a research vessel on the New Jersey continental shelf is employed to infer probability distributions for the parameter values representing the frequency dependence of the seabed attenuation and the source levels of the ship. The statistical inference approach employed in the analysis is a maximum entropy methodology. The average value of the error function, needed to uniquely specify a conditional posterior probability distribution, is estimated with data samples from time periods in which the ship-receiver geometry is dominated by either the stern or bow aspect. The existence of ambiguities between the source levels and the environmental parameter values motivates an attempt to partially decouple these parameter values. The main result is the demonstration that parameter values for the attenuation (α and the frequency exponent), the sediment sound speed, and the source levels can be resolved through a model space reduction technique. The results of this multi-step statistical inference developed for ship radiated noise is then tested by processing towed source data over the same bandwidth and source track to estimate continuous wave source levels that were measured independently with a reference hydrophone on the tow body.

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“…The idea is to select frequencies that have clearly identifiable modal interference patterns with about 5 maxima and minima over a time/range interval. 23 …”

Section: Stepmentioning

confidence: 99%

Maximum entropy inference of seabed attenuation parameters using ship radiated broadband noise

Knobles

2015

The Journal of the Acoustical Society of America

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“…Specifically, it is assumed to be temporally and frequentially white, zero mean and circularly-symmetric, i.e., (5) This model is justified by the large number of natural processes that can be modeled as stationary Gaussian random processes. The wideband noise generated by ships and submarines typically fall into this category [22]- [24]. Furthermore, randomness and variability of the ocean medium can be so important that the received signal is fully randomized and follows a Gaussian distribution even when the initial source signal is deterministic.…”

Section: Matched-field Problem Formulation and Data Modelmentioning

confidence: 99%

“…Based on the above result, the CDF of can be expressed as (24) with (25) for some such that . These results are now used to derive the pairwise error probability expressions.…”

Section: A Cumulative Distribution Function Of Quadratic Forms In Gamentioning

confidence: 99%

Matched-Field Processing Performance Under the Stochastic and Deterministic Signal Models

Gall

Socheleau

Bonnel

2014

IEEE Trans. Signal Process.

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International audienceMatched-field processing (MFP) is commonly used in underwater acoustics to estimate source position and/or oceanic environmental parameters. Performance prediction of the multisnapshot and multifrequency MFP problem is of critical importance. To this end, two signal models are usually considered: the stochastic model, which assumes that the source signal is a stochastic process, and the deterministic model, which assumes that the source signal is a deterministic quantity. The Ziv-Zakai bound (ZZB) and the method of interval errors (MIE), which both rely on the computation of a so-called pairwise error probability, proved to be useful tools for MFP performance prediction. However, only the stochastic model has been considered so far. This paper provides a method that allows to compute the pairwise error probability, hence to use the ZZB and MIE, under both the stochastic and deterministic signal models. The proposed approach, based on recent results on quadratic forms in Gaussian variables, unifies the two models under the same formalism. The results are illustrated through the computation of the ZZB and MIE performance analysis. The Bayesian and the hybrid Cramèr-Rao bounds are also given for comparison

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“…Assuming that the emitted noise is a unknown random process measured by a single sensor, correlation with the emitted signal or between measurements from several sensors [17][18][19][20][21][22][23] can not be used to pre-process the data and extract some observables. To cope with these limitations, we first compute the received level of the measurements.…”

Section: B Channel Propagation Featuresmentioning

confidence: 99%

“…[17][18][19][20][21] Sometimes, the CSDM are averaged over several frequency bandwidths. 22,23 However, the CSDM does not exploit the whole broadband nature of the noise radiated by a ship and the range aperture created by its movement.…”

Section: Introductionmentioning

confidence: 99%

Passive geoacoustic inversion with a single hydrophone using broadband ship noise

Gervaise

Kinda

Bonnel

et al. 2012

The Journal of the Acoustical Society of America

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An inversion scheme is proposed, relying upon the inversion of the noise of a moving ship measured on a single distant hydrophone. The spectrogram of the measurements exhibits striations which depend on waveguide parameters. The periodic behavior of striations versus range are used to estimate the differences of radial wavenumber between couples of propagative modes at a given frequency. These wavenumber differences are stacked for several frequencies to form the relative dispersion curves. Such relative dispersion curves can be synthesized using a propagation model feeded with a bottom geoacoustic model. Inversion is performed by looking for the bottom properties that optimize the fit between measured and predicted relative dispersion curves. The inversion scheme is tested on simulated data. The conclusions are twofold: (1) a minimum 6 dB signal to noise ratio is required to obtained an unbiased estimate of compressional sound speed in the bottom with a 3 m s(-1) standard deviation; however, even with low signal to noise ratio, the estimation error remains bounded and (2) in the case of a multi-layer bottom, the scheme produces a single depth-average compressional sound speed. The inversion scheme is applied on experimental data. The results are fully consistent with a core sample measured around the receiving hydrophone.

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Geoacoustic Inversions of Horizontal and Vertical Line Array Acoustic Data From a Surface Ship Source of Opportunity

Cited by 21 publications

References 29 publications

Maximum entropy inference of seabed attenuation parameters using ship radiated broadband noise

Maximum entropy inference of seabed attenuation parameters using ship radiated broadband noise

Matched-Field Processing Performance Under the Stochastic and Deterministic Signal Models

Passive geoacoustic inversion with a single hydrophone using broadband ship noise

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