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The U.S. Navy is enhancing its defense capabilities by leveraging cutting-edge AI to bolster laser weapon systems (LWS) against the rising threat of uncrewed autonomous systems (UAS). Researchers at the Naval Postgraduate School (NPS), in collaboration with Lockheed Martin, Boeing, and the Air Force Research Laboratory, are focusing on automating crucial components of the LWS tracking system to counter the growing threat of drone swarms.
Traditionally, operating an LWS to target and neutralize a hostile drone requires a sequence of detailed steps, including drone identification, pose estimation, and precise aimpoint selection. With the proliferation of drones, the Navy faces increasing challenges, especially when defending against multiple, low-cost drones compared to expensive missile interceptors. By integrating AI into the system, NPS researchers aim to reduce the time it takes to process these steps and improve overall targeting efficiency, according to TechXplore.
AI algorithms now automate processes like target classification, pose estimation, aimpoint selection and continuous aimpoint maintenance, which are essential when engaging a fast-moving drone. As drones can be unpredictable, especially under adverse environmental conditions, the task of keeping a laser beam focused on a moving target becomes even more challenging. By continuously adjusting the aimpoint to counter drone movement, laser weapon systems can ensure their maximum effectiveness in real-time engagements.
One key achievement in this research is the development of two comprehensive datasets for training AI models. The first consists of 100,000 synthetic images of drones, while the second includes 77,077 real-world images captured through the High Energy Laser Beam Control Research Testbed (HBCRT) at NPS. These datasets serve to train AI systems to recognize a drone’s specific pose and calculate its most vulnerable areas for laser targeting.
According to TechXplore, the HBCRT mimics a full-fledged LWS by employing a 30 cm diameter tracking telescope and a mid-wavelength infrared (MWIR) sensor, both mounted on a gimbal. The system uses the MWIR sensor to track a drone’s heat signature, while the telescope focuses the laser beam. The development of this system has already led to the successful application of AI-based automation, making it possible to use the system in semi-autonomous mode. An operator can now monitor the tracking process instead of manually managing it, thus enhancing efficiency and speed.
This AI-powered laser targeting system is also paving the way for future advancements. Through continuous field testing, including in collaboration with the Navy’s High Energy Laser Expeditionary (HELEX) system, these innovations will soon be deployed in real-world scenarios. As the Navy adapts to emerging threats, the integration of AI into directed energy systems offers a significant leap in defense capabilities, marking a new era for rapid, cost-effective countermeasures against drone warfare.
