Autonomous Sensing and Deciding Framework Processor

Toyon Research Corporation proposes to develop innovative algorithms for screening large volumes of intelligence data to autonomously highlight areas of interest for the research analyst. Toyon"s dual-level architecture will at the first level employ advanced data fusion and pattern recognition technologies to obtain long-term persistent tracks from SAR information data products. The fusion algorithms will provide persistent feature-aided tracking, target classification, and target fingerprinting to monitor and characterize each vehicle in the surveillance region. This set of tracks will supply the data from which behavioral features will be extracted. These long-term tracks and the behavioral features will feed a threat detection algorithm that will detect abnormal behaviors. In Phase I, Toyon will perform a feasibility study of the proposed solution by developing and extending component data fusion algorithms, designing the behavioral feature models, and evaluating anomaly detection performance to meet the specified technical objectives of the project.