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Prediction Method of the Low-Frequency Multistatic Scattering Sound Field for Underwater Spherical Targets Based on Limited Data

Authors :
CHEN Changxiong, PENG Zilong, SONG Hao, XUE Yaqiang, ZHOU Fulin
Source :
Shanghai Jiaotong Daxue xuebao, Vol 58, Iss 7, Pp 1006-1017 (2024)
Publication Year :
2024
Publisher :
Editorial Office of Journal of Shanghai Jiao Tong University, 2024.

Abstract

A prediction method based on the information data of finite scattering acoustic pressure is proposed for the prediction of underwater spherical target multistatic acoustic scattering sound field, which represents the scattering sound field as the product of the acoustic scattering transfer function and the source density function, obtains the acoustic scattering transfer function by numerical integration with the model surface grid information as input, and acquires the source density function by combining acoustic reciprocity, least squares, and matrix transformation with small amount of known scattered sound pressure data as input. The multistatic scattering sound field prediction method is validated by using the Rayleigh normal mode solution and the finite element method (FEM) for double-layered spherical shells and spherical shell with the.pngfener. The target strength experiment is conducted for the spherical shell with the.pngfener, and the experiment results are compared with the finite element calculations. Several test data and FEM calculation results data are used as input to predict the multistatic scattering sound field of the spherical shell with.pngfener and compared with the FEM results, respectively. It is found that the simulation and test results are in good agreement, which verifies the feasibility of the prediction method.

Details

Language :
Chinese
ISSN :
10062467
Volume :
58
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Shanghai Jiaotong Daxue xuebao
Publication Type :
Academic Journal
Accession number :
edsdoj.1b7b1ea52ac04dc6bb875d133b04a1cd
Document Type :
article
Full Text :
https://doi.org/10.16183/j.cnki.jsjtu.2022.463