Issue |
MATEC Web Conf.
Volume 283, 2019
The 2nd Franco-Chinese Acoustic Conference (FCAC 2018)
|
|
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Article Number | 06003 | |
Number of page(s) | 5 | |
Section | Physical Acoustics | |
DOI | https://doi.org/10.1051/matecconf/201928306003 | |
Published online | 28 June 2019 |
A method of geo-acoustic parameter inversion in shallow sea by the Bayesian theory and the acoustic pressure field
1 Institute of Marine Science and Technology, Zhejiang Ocean University, Zhejiang, 316022, China
2 Institute of Naval Architecture and Mechanical-electrical Engineering, Zhejiang Ocean University, Zhejiang, 316022, China
* Corresponding author: zhuhanhao@zjou.edu.cn
A method of geo-acoustic parameter inversion based on the Bayesian theory is proposed for the acquisition of acoustic parameters in shallow sea with the elastic seabed. Firstly, the theoretical prediction value of the sound pressure field is calculated by the fast field method (FFM). According to the Bayesian theory, we establish the misfit function between the measured sound pressure field and the theoretical pressure field. It is under the assumption of Gaussian data errors which are in line with the likelihood function. Finally, the posterior probability density (PPD) of parameters is given as the result of inversion. Our research is conducted in the light of Metropolis sample rules. Apart from numerical simulations, a scaled model experiment has been taken in the laboratory tank. The results of numerical simulations and tank experiments show that sound pressure field calculated by the result of inversion is consistent with the measured sound pressure field. Besides, s-wave velocities, p-wave velocities and seafloor density have fewer uncertainties and are more sensitive to complex sound pressure than s-wave attenuation and p-wave attenuation. The received signals calculated by inversion results are keeping with received signals in the experiment which verify the effectiveness of this method.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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