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The United States Air Force is tapping into the extensive expertise of Southwest Research Institute’s (SwRI) Advanced Electronic Warfare team with a $6.4 million contract to explore cognitive electronic warfare (EW) algorithms, which accurately detect and respond to unknown enemy radar threats in real time. SwRI engineers are conducting research to develop a reliable algorithm that will advance the Air Force’s cognitive EW capabilities and protect aircrews, SwRI announced April 2.
“How do we get to the point where the EW system is thinking like a human?” said SwRI staff engineer David Brown, who is leading the project. “A pilot can fly into an area and not know what’s there, but by analyzing the environment and signals, the pilot can choose a proper response to a threat. We are developing an algorithm that can analyze its environment the same way. It will sift through information with the reliability of a human, but with higher accuracy and faster reaction times.”
Traditional electronic warfare processes involve gathering intelligence before flying into an area. Aircraft operators have advance knowledge of which adversaries they might encounter, and that information is preloaded into the aircraft’s electronic warfare system. The system alerts pilots when it detects threats and automatically protects the aircraft. While this method is effective at tracking known threat signals, the system is incapable of identifying never-before-seen threats. That’s where cognitive EW could prove a stronger, faster and more accurate tool to protect the warfighter and enhance capabilities with allies.
“In the past, we’ve relied on a library of signals that allows you to recognize and compare familiar signals. We’re asking, ‘does this match anything I already know about?’” said SwRI research engineer Damon Plyler, who is part of the development team. “That library is the limit of our information. Through cognitive EW and a machine learning approach, we can instantly identify new signals that are not already in the library.”
To develop this autonomous EW system, SwRI engineers are using a two-phased approach. The first phase, feature extraction, uses artificial intelligence and machine learning processes to extract specific features of threatening radar signals. Those data are used in the second phase to group millions of pulses, highlighting signal lethality and vulnerabilities.
SwRI engineers are implementing feature extraction algorithms on advanced platforms, including neuromorphic processing hardware. Neuromorphic computing systems use spiking neural networks to emulate how the human brain retains “memories,” making processing faster, more accurate and efficient.
“We are working to provide the Air Force with efficient and resilient cognitive EW solutions,” said SwRI’s Dr. Steven Harbour, who is applying his doctorate in neuroscience to lead the development of neuromorphic systems. “We are implementing neuromorphics in hardware to be used for the first time in an operational combat environment. It puts us well ahead of our adversaries. To the best of our knowledge, we are the first in the world to do this.”
SwRI’s cognitive EW work began as a multiyear, multimillion-dollar internal research and development (IR&D) project. Through its IR&D program, the Institute invests in future-focused concepts to advance technology for government and industry clients. The contract between SwRI and USAF commenced on October 1, 2023, and will run through March 2025. Upon completion of the project, SwRI will present the Air Force with effective research toward advancing the field of cognitive EW.
Source: SwRI
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