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

Applied and Computational Mathematics Seminar
Monday, November 21, 2016 - 14:05
1 hour (actually 50 minutes)
Skiles 005
Georgia Tech Mathematics
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 \r{pre-computed} library of representative acoustic responses from various seafloor parameterizations.