Radar Mission Autonomy for Congested and Contested Environments

The Air Force needs “on-demand awareness of adversary actions," as stated in U.S. Air Force, Science and Technology Strategy: Strengthening USAF Science and Technology for 2030 and Beyond. A vital part of meeting this need is employing covert Intelligence, Surveillance, and Reconnaissance (ISR) solutions in both Anti-Access/Area Denial (A2/AD) environments as well as congested environments. IMSAR LLC proposes to develop a mission autonomous system for low-cost, low-Size, Weight, and Power (SWaP) radars that can perform ISR and targeting functions in a variety of environments. This would include regions with multiple in-band radars operating as well as A2/AD environments, which can present their own unique set of challenges.  Adding Mission Autonomy (MA) through Artificial Intelligence (AI) and Machine Learning (ML) will allow radar systems to maintain quality ISR in near-peer conflicts.  The proposed MA system will utilize adversarial ML techniques to change frequencies on the fly for spectrum deconfliction when multiple systems are operating, to switch waveforms when appropriate, and to continue to provide high quality data and intelligence in the midst of interference.  During Phase I, IMSAR LLC proposes to conduct customer and feasibility research, and to explore adding the MA capability, previously called cognitive radar.