Abstract
In May 2014, the MIT Laboratory for Autonomous Marine Sensing Systems (LAMSS) participated in the BAYEX'14 experiment with the goal of collecting full bistatic data sets around proud spherical and cylindrical targets for use in real-time autonomous target localization and classification. The BAYEX source was set to insonify both targets, and was triggered to ping at the start of each second using GPS PPS. The MIT Bluefin 21 in. AUV Unicorn, fitted with a 16-element nose array, was deployed in broadside sampling behaviors to collect the bistatic scattered data set. The AUV's Chip Scale Atomic Clock was synchronized to GPS on the surface, and the data was logged using a PPS triggered analog to digital conversion system to ensure synchronization with the source. The MIT LAMSS operational paradigm allowed the vehicle to be unpacked, tested and deployed over the brief three-day interval available for operations. MOOS-IvP and acoustic communication enabled the group to command AUV mission changes in situ based on data collection needs. During data collection, the vehicle demonstrated real-time signal processing and target localization, and the bistatic datasets were used to demonstrate real-time target classification in simulation. [Work supported by ONR Code 322OA.]
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