Sensor Fusion for Situation Awareness in Littoral Environments

To support pilot situation awareness for small high-speed submersibles in littoral environments, automatic information fusion is needed that is capable off deriving actionable information from sensor data that is degraded in the manner of sonar data in shallow water. A Phase I project showed the feasibility of using technology for automated abductive inference (best explanation reasoning), supported by modeling and simulation, to detect, and infer the locations of, sonically illuminated objects, using data from ambient sounds that have been degraded by multipathing. It appears that 3D scene reconstruction from passive (and active) sonar can be done using layered abductive inference, physics models, computational geometry, and miscellaneous domain knowledge. The objectives of the Phase II project are to develop a more advanced abduction engine and to demonstrate its effectiveness for 3D scene reconstruction from passive sonar. Model-based abduction has many potential applications to other problems of information fusion and interpretation for military and civilian applications.