US Navy Deploys AI-Powered Laser Weapons to Combat Drone Swarm Threats
Image Source: Military World | Youtube
The US Navy is taking a major step forward in automating countermeasures against drone swarm attacks by integrating artificial intelligence into laser weapon systems. This initiative, led by the Naval Postgraduate School (NPS) in collaboration with the Naval Surface Warfare Center Dahlgren Division, Lockheed Martin, Boeing, and the Air Force Research Laboratory (AFRL), aims to enhance the accuracy and efficiency of laser-based defenses by reducing reliance on human operators.
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The Growing Threat of Drone Swarms
With the increasing sophistication of drone technology, military forces worldwide are looking for reliable countermeasures to defend against aerial threats. Lasers offer a promising solution, as they can engage targets at the speed of light without the need for ammunition. However, the challenge lies in their operational effectiveness—especially when facing swarms of autonomous drones that can quickly overwhelm a human operator.
The process of neutralizing a drone requires two critical steps: identifying the type of drone and determining its structural weak points, followed by maintaining a laser beam on the target long enough to disable it. While a skilled operator may be able to track and destroy a single drone, handling an entire swarm is an overwhelming task.
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AI-Powered Target Identification and Tracking
To overcome the limitations of human-controlled targeting, the research team has developed an AI-based tracking system designed to improve laser accuracy. The system was trained using a miniature, 3D-printed titanium model of a Reaper drone. This model was scanned using infrared and radar imaging to simulate real-world conditions, generating two datasets with a total of 100,000 images.
These datasets were then used to train AI algorithms capable of recognizing drones from various angles and distances, even under suboptimal visibility conditions. The AI is programmed to assess the drone's orientation, identify its weak spots, and direct laser beams with precision. Radar inputs further enhance the system's ability to track movement and distance, ensuring real-time adaptability in combat scenarios.
Training and Performance Evaluation
To validate the AI system, researchers employed three training scenarios:
Using only synthetic data.
Using a combination of synthetic and real-world data.
Using exclusively real-world data.
According to the US Navy, the third approach—relying entirely on real-world data—produced the most accurate results with minimal errors.
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Field Testing and Future Applications
The next phase of development involves live field testing with radar and optical tracking of real targets. Initially, the system will operate in a semi-autonomous mode, where human operators will retain some control over the tracking process. Eventually, the goal is to transition toward a fully autonomous system capable of responding to threats with minimal human intervention.
Eric Montag, an imaging scientist at Dahlgren, confirmed that the AI model is now functional within their tracking system. A proof-of-concept demonstration is scheduled for later this year, where the AI’s automatic aimpoint selection capabilities will be tested within an operational framework. Importantly, the tests will not require actual laser deployment to assess targeting precision. The AI-powered tracking system is also being integrated with other military initiatives, such as the High Energy Laser Expeditionary (HELEX) demonstrator program.
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Challenges and Considerations
Despite its promise, AI-driven laser weapons face several technical and ethical challenges. Atmospheric distortions can impact laser precision over long distances, requiring further refinements in adaptive optics. Additionally, while AI can significantly improve targeting efficiency, fully autonomous weapons raise concerns regarding accountability and decision-making in combat scenarios. The balance between human oversight and AI automation remains a critical discussion point in military strategy.
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Source: New Atlas
