Data-driving machine learning algorithms to be developed by BAE Systems for DARPA program
NewsNovember 27, 2018
BURLINGTON, Mass. U.S. Defense Advanced Research Projects Agency (DARPA) officials selected BAE Systems for a contract valued at $9.2 million to develop new, data-driving machine learning algorithms for its Radio Frequency Machine Learning System (RFMLS) program.
Under this Phase 1 contract, BAE Systems’ scientists intend to create machine learning algorithms, using cognitive approaches, that will use feature learning techniques to differentiate signals. In addition, researchers aim to create algorithms that can learn to differentiate important versus unimportant signals in real-time scenarios through a deep learning approach.
The technology being developed for the RFMLS program is part of the machine learning and artificial intelligence research focus area within the company’s autonomy technology portfolio, and adds to previous work in this area, including the DARPA Communications Under Extreme RF Spectrum Conditions (CommEX) and Adaptive Radar Countermeasures (ARC) programs. BAE Systems has also advanced to the second round of another major DARPA effort to bring machine learning and artificial intelligence to the RF domain called the Spectrum Collaboration Challenge (SC2).
“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,” says Dr. John Hogan, product line director of the Sensor Processing and Exploitation product line at BAE Systems. “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.”
Work for the RFMLS program is being done by the research and development team at BAE Systems’ facilities in Burlington, Massachusetts, and Durham, North Carolina.
