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

摘要

We present a multiscale approach for identifying features in ocean beds bysolving inverse problems in high frequency seafloor acoustics. The setting isbased on Sound Navigation And Ranging (SONAR) imaging used in scientific,commercial, and military applications. The forward model incorporatesmultiscale simulations, by coupling Helmholtz equations and geometrical opticsfor a wide range of spatial scales in the seafloor geometry. This allows fordetailed recovery of seafloor parameters including material type. Simulatedbackscattered data is generated using numerical microlocal analysis techniques.In order to lower the computational cost of the large-scale simulations in theinversion process, we take advantage of a pre-computed library ofrepresentative acoustic responses from various seafloor parameterizations.