New research by BAE Systems for DARPA is expected to help decipher the growing number of RF signals, which may help both commercial and military users improve situational awareness. Photo courtesy of BAE
Nov. 27 (UPI) -- BAE Systems has been selected by the U.S. Defense Advanced Research Projects Agency to develop machine learning algorithms to decipher radio frequency signals for protection against enemy hacking and jamming attempts.
DARPA is awarding BAE $9.2 million for machine learning algorithm development, the company announced on Tuesday, which will build off of adaptive technology that has already been applied to face- and voice-recognition systems and drones operating autonomously for RF signal processing.
"The inability to uniquely identify signals in an environment creates operational risk due to the lack of situational awareness, inability to target threats, and vulnerability of communications to malicious attack," Dr. John Hogan, product line director of BAE Systems Sensor Processing and Exploitation division, said in a press release.
"Our goal for the RFMLS program is to create algorithms that will enable a whole new level of understanding of the RF spectrum so users can identify and react to any signals that could be putting them in harm's way," Hogan said.
Under the Phase 1 contract, BAE will develop the RFMLS as part of its artificial intelligence efforts utilizing technology from DARPA's Communications Under Extreme RF Spectrum Conditions and Adaptive Radar Countermeasures programs.
BAE Systems is already working on DARPA's machine learning and artificial intelligence research in RF called the Spectrum Collaboration Challenge.
SCC is meant to help alleviate scarcities in available RF spectrum, which would dovetail with work being performed on RFMLS by identifying spectrum that could evade enemy jamming.
