RF-IR Data Fusion

The development and integration of three unique and innovative algorithm prototypes into a"Fused Track and Characterization Schema"are proposed. This Schema will encompass the determination of signatures and characteristics of objects that can be identified by RF and EO/IR Sensors in order to enable multi-sensor data fusion and correlation. The first algorithm, the"3D Pose Estimation"Algorithm, permits track and correlation of multiple objects using multisensory EO/IR data measurements. The second algorithm,"Wager"correlates multiple RF and sensor measurements with the EOIR"Pose"solution to generate system level tracks."Wager"is based on automated Best Estimate of Truth methods. The third algorithm,"Fused TASM"uses fused Target Attributes Surface Manifold Classifiers to characterize and associate targets across multiple sensors. TASM Classifiers, inherently by design, embed physical relationships between multiple sensor phenomenologies. The TASM Classifier construction is based on advanced Computer Graphics NURBS methods.