Optimizing Position, Navigation, and Timing (PNT) data goes a long way for the warfighter in theater. It ensures they have the most accurate navigation information possible and helps drive mission readiness. So, finding ways to continue improving the collection and management of that data is, of course, appealing to the defense community. A prime example is how the U.S. Marine Corps is looking to machine learning to up the ante with how they harness the power of PNT data, allowing them to more quickly detect spoofing and jamming efforts.
According to a recent Via Satellite article, Jim Baker, senior principal engineer for the Marine Corps Tactical Systems Support Activity (MCTSSA), a subordinate command of Marine Corps Systems Command located at Camp Pendleton, California, thinks the defense community could be taking much better advantage of the PNT data available to it and using machine learning to help fight adversarial spoofing and jamming. “I can record data…with well over 2,000 bits of information every second,” Baker said.
Leveraging data available from all of the sensors and PNT receivers and machine learning to identify attempted spoofing or jamming threats and, in turn, reducing the time of threat detection can be crucial to the warfighter. Currently that data is overlooked, but when put to use, it offers an opportunity to further sharpen situational awareness for the warfighter and potentially shave off hours of time and intelligence lost due to jamming.
“If I can find out and detect the jamming … from when it’s first detected by my receiver and starts collecting data or analyzing that, or at least recognize that there’s jamming going on – even before it actually affects my PNT solution – then I can do something about it,” Baker stated.