In today’s wireless world, the radio frequency (RF) spectrum is exploding in complexity—posing new levels of malicious threats to national security. Pacific Northwest National Laboratory (PNNL) is developing solutions to defend against RF-enabled espionage and cyberattacks on government facilities, critical infrastructure, aviation, telecommunications systems, and other vital RF-enabled environments.
Blending multidisciplinary expertise in RF, cybersecurity, computing, and data science—with core strengths in artificial intelligence and machine learning (AI/ML)—our scientists and engineers are developing novel capabilities that will increase our ability to confidently understand, control, and protect RF environments.
Real-time RF signal detection
RF interference can threaten a variety of commonly used wireless technologies on which many aspects of national security depend, such as land mobile radio, Bluetooth, wi-fi, and Global Positioning Systems. Protecting our nation’s secure RF environments requires improved technical surveillance and countermeasure tools for real-time analysis and response of radio frequencies and other suspicious signals.
In collaboration with government sponsors, PNNL researchers are developing a next-generation, in-place RF monitoring system—or IPMS—to better protect government facilities against RF-enabled threats. Bringing together high-performance sensors and sophisticated machine learning algorithms, this monitoring technology can rapidly detect and assess signal an1omalies in and around secure environments—enabling faster, more effective response to RF interference.
Through this project and other research, we are advancing the nation’s understanding of the swiftly evolving RF spectrum and developing leading-edge capabilities to detect and exploit RF in support of our national security mission.