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

Björn Engquist, Christina Frederick, Quyen Huynh, Haomin Zhou

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)477-492
Number of pages16
JournalJournal of Computational Physics
Volume338
DOIs
StatePublished - Jun 1 2017

All Science Journal Classification (ASJC) codes

  • Numerical Analysis
  • Modeling and Simulation
  • Physics and Astronomy (miscellaneous)
  • Physics and Astronomy(all)
  • Computer Science Applications
  • Computational Mathematics
  • Applied Mathematics

Keywords

  • Discrete optimization
  • Inverse problems in underwater acoustics
  • Multiscale modeling
  • SONAR imaging
  • Wave propagation

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