Cognitive Software Algorithms Techniques for Electronic Warfare

Vadum will implement a cognitive threat characterization system (CTCS) for transition to the Aegis Weapons System (AWS). The CTCS employs a learning framework and feature extraction algorithms to more accurately detect, classify, and predict agile, adaptive threats using both RF and kinematic properties. CTCS will leverage data products from a variety of AWS sensors. Vadum has demonstrated that disparate sensor data sources can augment threat detection, identification, and intent estimation, enabling highly accurate prediction of future threat behavior in each of the RF and kinematic domains. Over the course of the Phase II effort, Vadum will develop a capability to fuse these sensor data sources, leading to behavioral prediction and threat track evolution with still higher accuracy, providing hard kill/soft kill coordination and engagement decisions with greater lethality.