Seafloor identification in sonar imagery via simulations of Helmholtz equations and discrete optimization

JOURNAL OF COMPUTATIONAL PHYSICS

卷:338

Article

Engquist, Bjorn¹  Frederick, Christina²  Huynh, Quyen³  Zhou, Haomin² 

[1] Univ Texas Austin, Dept Math, Austin, TX 78712 USA

[2] Georgia Inst Technol, Sch Math, Atlanta, GA 30332 USA

[3] Brown Univ, Inst Brain & Neural Syst, Providence, RI 02912 USA

关键词: Inverse problems in underwater acoustics;    SONAR imaging;    Multiscale modeling;    Wave propagation;    Discrete optimization;   

DOI  :  10.1016/j.jcp.2017.03.004

来源: Elsevier

【 摘 要 】

We present a multiscale approach for identifying features in ocean beds by solving inverse problems in high frequency seafloor acoustics. The setting is based on Sound Navigation And Ranging (SONAR) imaging used in scientific, commercial, and military applications. The forward model incorporates multiscale simulations, by coupling Helmholtz equations and geometrical optics for a wide range of spatial scales in the seafloor geometry. This allows for detailed recovery of seafloor parameters including material type. Simulated backscattered data is generated using numerical microlocal analysis techniques. In order to lower the computational cost of the large-scale simulations in the inversion process, we take advantage of a pre-computed library of representative acoustic responses from various seafloor parameterizations. (C) 2017 Elsevier Inc. All rights reserved.

【 授权许可】

Free