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Research Article | Open Access

Shape reconstruction of acoustic obstacle with linear sampling method and neural network

Bowen Tang1, Xiaoying Yang1( ), Lin Su2
School of Mathematics and Statistics, Changchun University of Technology, 3000. Beiyuanda Ave, Changchun, Jilin 130000, China
Wuxi Weintdata Technology Co. Ltd, 2. Longshan Rd, Wuxi, Jiangsu 214000, China
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Abstract

We consider the inverse scattering problem of reconstructing the boundary of an obstacle by using far-field data. With the plane wave as the incident wave, a priori information of the impenetrable obstacle can be obtained via the linear sampling method. We have constructed the shape parameter inversion model based on a neural network to reconstruct the obstacle. Numerical experimental results demonstrate that the model proposed in this paper is robust and performs well with a small number of observation directions.

Keywords

inverse acoustic scattering problemslinear sampling methodneural networkshape reconstruction of obstacles
CLC number: 65B99, 68T07

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AIMS Mathematics
Volume 9 Issue 6,
May 2024
Pages 13607-13623
DOI: 10.3934/math.2024664

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Cite this article:
Tang B, Yang X, Su L. Shape reconstruction of acoustic obstacle with linear sampling method and neural network. AIMS Mathematics, 2024, 9(6): 13607-13623. https://doi.org/10.3934/math.2024664

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Received: 03 February 2024
Revised: 29 March 2024
Accepted: 07 April 2024
Published: 12 April 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)