Naval Postgraduate School (NPS) researchers and collaborators are applying AI to automate critical parts of the tracking system used by laser weapon systems (LWS) for the US Navy.
Funded by the Joint Directed Energy Transition Office (DE-JTO) and the Office of Naval Research (ONR), this research addresses advanced AI and directed energy technology applications cited in the CNO NAVPLAN.
The tracking system of an LWS follows a sequence of demanding steps to successfully engage an adversarial UAS. When conducted by a human operator, the steps can be time-consuming, especially when facing numerous drones in a swarm. There are also the challenges of an adversary’s missiles and rockets traveling at hypersonic speeds, so the efforts to mount proper defenses become even more complicated and urgent.
Directed energy and AI are both considered DOD-critical technology areas. By automating and accelerating the sequence for targeting drones with an AI-enabled LWS, a research team from NPS, Naval Surface Warfare Center Dahlgren Division, Lockheed Martin, Boeing and the Air Force Research Laboratory (AFRL) developed an approach to have the operator on-the-loop overseeing the tracking system instead of in-the-loop manually controlling it.
To achieve this level of automation, the researchers generated two datasets that contained thousands of drone images and then applied AI training to the datasets. This produced an AI model that was validated in the laboratory and then transferred to Dahlgren for field testing with its LWS tracking system.
“Defending against one drone isn’t a problem. But if there are multiple drones, then sending million-dollar interceptor missiles becomes a very expensive tradeoff because the drones are very cheap,” said Distinguished Professor Brij Agrawal , NPS Department of Mechanical and Aerospace Engineering, who leads the NPS team.
“The Navy has several LWS being developed and tested. LWS are cheap to fire but expensive to build. But once it’s built, then it can keep on firing, like a few dollars per shot.”
Overall, the AI model from the scenario using only the real-world dataset performed best by producing the least amount of error, according to the researchers. For the next phase of the research, the team transferred the AI model to Dahlgren for field-testing on its LWS tracking system.
Besides LWS, this research also opens other possibilities for use throughout the fleet. Tracking systems across other platforms could also see potential benefits from this type of AI-enabled automation, it was concluded.
To remind, in 2022, the US Navy carried out a ‘historic test’ of an all-electric, high-energy laser weapon to defeat a target representing a subsonic cruise missile in flight.