Utilizing Autonomous Underwater Vehicles for Seafloor Mapping, Target Identification, and Predictive Model Testing

摘要

Our long term goals are: (1) to develop/improve inversion techniques for normal-incidence sediment classification systems and remotely determine sediment physical and geoacoustic properties and (2) to determine mechanisms responsible for scattering of high-frequency energy. Our objectives are to identify mine burial mechanisms in shallow water environments subject to tidal and wave-induced currents and to test existing predictive burial models with AUV-acquired environmental parameters. These objectives are pursued jointly with the University of South Florida (USF) and Florida Atlantic University (FAU) so as to provide the site characterization and AUV components necessary for the experiment. We must remotely classify sediments for mine burial prediction sing the 2-12 kHz chirp subbottom profiler and predict acoustic reverberation using the chirp sidescan system. These systems can be used to image buried (or proud) inert mines. By collecting ground-truth data with divers together with the remote sediment classification data we can test existing predictive mine burial models. Use of an instrumented mine analogue to monitor the results of hydrodynamic stress on the seabed is an essential portion of the model validation effort.