Autonomous Wide Aperture Cluster for Surveillance (AWACS): Adaptive Sampling and Search Using Predictive Models with Coupled Data Assimilation and Feedback

摘要

This research aims to develop and evaluate new environmental- acoustical adaptive sampling and search methodologies, and improve the modeling of ocean dynamics, for the environments in which the main AWACS experiments will occur, using the re-configurable REMUS cluster and coupled data assimilation. Specific objectives are to: (i) Evaluate current methods and develop new algorithms for adaptive environmental-acoustical sampling, search and coupled data assimilation techniques (Stage 1), based on a re-configurable REMUS cluster and on idealized and realistic simulations (with NPS/OASIS/Duke) (ii) Research optimal REMUS configurations for the sampling of interactions of the oceanic mesoscale with inertial oscillations, internal tides and boundary layers (with WHOI/NPS/OASIS) (iii) Improve models of (sub)-mesoscale ocean physics and develop new adaptive ocean model parameterizations for specific regional AWACS processes. Study and compare processes and dynamics in these regions (with WHOI) (iv) Provide near real-time fields and uncertainties in AWACS experiments and, in the final 2 years, develop algorithms for coupled physical-acoustical data assimilation among relocatable nested 3D physical and 2D acoustical domains (with NPS) (v) Provide adaptive sampling guidance for array performance and surveillance (Stage 2), and link our MIT research with vehicle models and command and control.