A Method for Estimating Dominant Acoustic Backscatter Mechanism of Water-Seabed Interface via Relative Entropy Estimation

Many geoacoustic models are used to establish the relationship between the physical and acoustic properties of sediments. In this work, Bayesian inversion and model selection techniques are applied to compare combinations of three geoacoustic models and corresponding scattering models—the fluid model with the effective density fluid model (EDFM), the grain-shearing elastic model with the viscosity grain-shearing (VGS(λ)) model, and the poroelastic model with the corrected and reparametrized extended Biot–Stoll (CREB) model. First, the resolution and correlation of parameters for the three models are compared based on estimates of the posterior probability distributions (PPDs), which are obtained by Bayesian inversion using the backscattering strength data. Then, model comparison and selection techniques are utilized to assess the matching degree of model predictions and measurements qualitatively and to ascertain the Bayes factors in favor of each quantitatively. These studies indicate that the fluid and poroelastic models outperform the grain-shearing elastic model, in terms of both parameter resolution and the ability to produce predictions in agreement with measurements for sandy sediments. The poroelastic model is considered to be the best, as the inversion based on it can provide more highly resolved information of sandy sediments. Finally, the attempt to implement geoacoustic inversion with different models provides a relatively feasible remote sensing scheme for various types of sediments under unknown conditions, which needs further validation.

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“…The authors declare no conflict of interest. The in-water wave vectors of incident and scattered directions are defined as follows [63]:…”

Section: Fundingmentioning

confidence: 99%

A Comparison of Three Sediment Acoustic Models Using Bayesian Inversion and Model Selection Techniques

Zou

Zhai

et al. 2019

Remote Sensing

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“…Since the backscattering strength measurements have two different frequencies (25 and 35 kHz), we have carried out three different inversions, comprising two inversions based on two sets of single-frequency scattering strength data and one inversion based on a dual-frequency scattering strength data set. Indeed, compared with DREAM, which has been applied to geoacoustic inversion [37,38], the convergence efficiency of MT-DREAM (ZS) is greatly improved, and we will not repeat the comparison of the two. This is not the focus of this paper, and a detailed comparison is available in [33].…”

Section: Geoacoustic Inversionmentioning

confidence: 99%

“…Therefore, it is necessary to introduce a more efficient and accurate method for solving PPD into Bayesian inversion. Although the original DREAM methods have been successfully applied to geoacoustic inversion to evaluate the main scattering mechanism and select the model that best matches the measurements [37,38], the inversion results based on DREAM have not been verified by field measurements.…”

Section: Introductionmentioning

confidence: 99%

Integrating Multiple-Try DREAM(ZS) to Model-Based Bayesian Geoacoustic Inversion Applied to Seabed Backscattering Strength Measurements

Zou

Hou

et al. 2019

JMSE

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The key to model-based Bayesian geoacoustic inversion is to solve the posterior probability distributions (PPDs) of parameters. In order to obtain PPDs more efficiently and accurately, the state-of-the-art Markov chain Monte Carlo (MCMC) method, multiple-try differential evolution adaptive Metropolis(ZS) (MT-DREAM(ZS)), is integrated to the inverse problem because of its excellent ability to fully explore the posterior space of parameters. The effective density fluid model (EDFM), which is derived from Biot–Stoll theory to approximate the poroelastic model, and the published field measurements of backscattering strength are adopted to implement the inversion. The results show that part of the parameters can be estimated close to the measured values, and the PPDs obtained by dual-frequency inversion are more concentrated than those of single-frequency inversion because of the use of more measured backscattering strength data. Otherwise, the comparison between the predicted backscattering strength of dual-frequency inversion results and Jackson’s prediction shows that the solutions of the inverse problem are not unique and may have multiple optimal values. Indeed, the difference between the two predictions is essentially the difference in the estimation of the contribution of volume scattering to the total scattering. Nevertheless, both results are reasonable due to the lack of measurement of volume scattering parameters, and the inversion results given by the posterior probabilities based on the limited measurements and the adopted model are still considered to be reliable.

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Accelerated Deconvolved Imaging Algorithm for 2D Multibeam Synthetic Aperture Sonar

Wei

Xing

et al. 2022

Sensors

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High-accuracy level underwater acoustical surveying plays an important role in ocean engineering applications, such as subaqueous tunnel construction, oil and gas exploration, and resources prospecting. This novel imaging method is eager to break through the existing theory to achieve a higher accuracy level of surveying. Multibeam Synthetic Aperture Sonar (MBSAS) is a kind of underwater acoustical imaging theory that can achieve 3D high-resolution detecting and overcome the disadvantages of traditional imaging methods, such as Multibeam Echo Sounder (MBES) and Synthetic Aperture Sonar (SAS). However, the resolution in the across-track direction inevitably decreases with increasing range, limited by the beamwidth of the transducer array of MBES. Furthermore, the sidelobe problem is also a significant interference of imaging sonar that introduces image noise and false peaks, which reduces the accuracy of the underwater images. Therefore, we proposed an accelerated deconvolved MBSAS beamforming method that introduces exponential acceleration and vector extrapolation to improve the convergence velocity of the classical Richardson-Lucy (R-L) iteration. The method proposed achieves a narrow beamwidth with a high sidelobe ratio in a few iterations. It can be applied to actual engineering applications, which breaks through the limitation of the actual transducer array scale. Simulations, tank, and field experiments also demonstrate the feasibility and advantages of the method proposed. 3D high-accuracy level underwater acoustical surveying can be achieved through this 2D MBES transducer array system, which can be widely promoted in the field of underwater acoustical remote sensing.

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A Method for Estimating Dominant Acoustic Backscatter Mechanism of Water-Seabed Interface via Relative Entropy Estimation

Cited by 3 publications

References 28 publications

A Comparison of Three Sediment Acoustic Models Using Bayesian Inversion and Model Selection Techniques

A Comparison of Three Sediment Acoustic Models Using Bayesian Inversion and Model Selection Techniques

Integrating Multiple-Try DREAM(ZS) to Model-Based Bayesian Geoacoustic Inversion Applied to Seabed Backscattering Strength Measurements

Accelerated Deconvolved Imaging Algorithm for 2D Multibeam Synthetic Aperture Sonar

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