Signal Processing and Data Fusion for Autonomous Undersea Vehicles

Abstract

The strategic and tactical applications for autonomous submersibles place great demands on the platforms' passive sonar signal and data processing abilities. It is necessary to overcome the limited acoustic aperture and lack of human supervision by exploiting synergism between front-end signal processing functions and back-end data fusion algorithms. An Information Management System Architecture is presented which represents the relationship between the Information Extraction (signal processing and data fusion), Situation Assessment, and Mission Planner. The information extraction requirements (essentially the emulation of manned platform detection, classification, and localization) drive the design of the signal and data processing architectures. The signal processing architecture is partitioned into a generic, multifunction (e.g. sonar, comm, navigation) processor complemented by an ancillary signal processor which supports the knowledge-based signal interpretation function of information fusion.