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

Bowen Tang; Xiaoying Yang; Lin Su; Bowen Tang; Xiaoying Yang; Lin Su

doi:10.3934/math.2024664

AIMS Mathematics

2024, Volume 9, Issue 6: 13607-13623. doi: 10.3934/math.2024664

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

1.
School of Mathematics and Statistics, Changchun University of Technology, 3000. Beiyuanda Ave, Changchun, Jilin 130000, China
2.
Wuxi Weintdata Technology Co. Ltd, 2. Longshan Rd, Wuxi, Jiangsu 214000, China

Received: 03 February 2024 Revised: 29 March 2024 Accepted: 07 April 2024 Published: 12 April 2024
MSC : 65B99, 68T07

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.
- inverse acoustic scattering problems,
- linear sampling method,
- neural network,
- shape reconstruction of obstacles
Citation: Bowen Tang, Xiaoying Yang, Lin Su. Shape reconstruction of acoustic obstacle with linear sampling method and neural network[J]. AIMS Mathematics, 2024, 9(6): 13607-13623. doi: 10.3934/math.2024664

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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.

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