  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.
