US Navy Uses AI To Train Laser Weapons Against Drones

The US Navy is taking a step toward fully autonomous defense systems by integrating AI into its laser weapons. This advancement, spearheaded by the Naval Postgraduate School (NPS) in collaboration with Lockheed Martin, Boeing, and other defense agencies, aims to improve laser targeting capabilities against drone swarms.

Lasers are emerging as a promising solution for countering aerial threats due to their speed and precision. However, their effectiveness has been limited by the reliance on human operators who must identify targets, locate weak spots, and keep the beam focused long enough to neutralize threats. While a single drone can still be managed manually, an incoming swarm presents an overwhelming challenge.

To address these limitations, the research team trained an AI system to enhance laser targeting accuracy. Using a 3D-printed titanium model of a Reaper drone, they simulated real-world targeting conditions by scanning the model with infrared and radar imaging. This process created a vast dataset of 100,000 images, enabling the AI to learn how to recognize drones, determine their position, and precisely focus the laser on their most vulnerable areas. The study explored three training approaches: one relying solely on synthetic data, another combining synthetic and real-world data, and a final test using only real-world data. The last approach proved to be the most effective, delivering the best results with minimal errors.

Following these successful simulations, the next phase involves live field testing. The AI-driven tracking system will be integrated into real-world military operations, allowing for radar and optical tracking of actual targets. Initially, the system will operate in a semi-autonomous mode, with human operators overseeing certain aspects of targeting to ensure reliability.