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Open AccessArticle

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

1
School of Marine Science and Technology, Tianjin University, Tianjin 300072, China
2
National Ocean Technology Center, Tianjin 300112, China
3
Institute of Geospatial Information, Information Engineering University, Zhengzhou 450052, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(5), 562; https://doi.org/10.3390/rs11050562
Received: 15 January 2019 / Revised: 21 February 2019 / Accepted: 2 March 2019 / Published: 7 March 2019
(This article belongs to the Special Issue Advances in Undersea Remote Sensing)
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. View Full-Text
Keywords: geoacoustic models; Bayesian inversion; backscattering strength; sandy sediments; Bayes factor geoacoustic models; Bayesian inversion; backscattering strength; sandy sediments; Bayes factor
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MDPI and ACS Style

Zou, B.; Zhai, J.; Qi, Z.; Li, Z. A Comparison of Three Sediment Acoustic Models Using Bayesian Inversion and Model Selection Techniques. Remote Sens. 2019, 11, 562.

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