Machine Learning-based Waveform Embedded System for Agnostic Countermeasures

To address the Army’s need for countermeasures to electronic warfare (EW) attacks on communications systems to increase EW resilience, Physical Optics Corporation (POC) proposes to develop a new Machine Learning-based Waveform Embedded System for Agnostic Countermeasures (MAC) in tactical radios. MAC innovatively integrates POC-developed mature algorithms to provide tactical radios with increased EW resilience. MAC employs artificial intelligence based on deep machine learning to issue the correct EW countermeasure response without a-priori information regarding the nature of the attack. As a result, MAC is an advanced EW countermeasure that directly addresses the Army’s requirements for increased EW resilience and is a practical, fieldable tactical solution. In Phase I, POC will demonstrate the feasibility of MAC by demonstrating the ability of MAC’s algorithms to recognize when tactical waveforms experience an EW attack and respond within 5 min to counter the attack without a-priori information regarding the nature of the attack, reaching technology readiness level (TRL)-4/5. In Phase II, POC plans to demonstrate MAC within a relevant environment, running independently to any particular radio acquisition effort, reaching TRL-6/7.