ThayerMahan Tracks UUVs at Navy Lanternfish 26 Exercise

August 12, 2026
ThayerMahan said its acoustic intelligence systems detected, classified, localized, and tracked all UUV classes used during Exercise Lanternfish 26.

ThayerMahan said in a press release that it deployed distributed acoustic intelligence systems and software during Exercise Lanternfish 26, where its systems detected, classified, localized, and tracked all UUV classes used in the exercise. The company said the vehicles ranged from a six inch diameter system to XLUUV class systems.

For the exercise, ThayerMahan deployed fixed ShorePicket™ and mobile Outpost® sensing systems. Its TransparenSea® software processed acoustic data, displayed tracks for operators, and exported detections to Navy Common Operating Pictures in real time.

The company said both systems were operational in less than 24 hours, required no specialized installation equipment, and did not disrupt normal port activity. It also said the systems maintained performance during heavy harbor traffic, including a vessel that idled over the array for an extended period.

We hope you enjoyed this article.

Consider subscribing to one of our newsletters like Defense AI Brief or Daily AI Brief.

Also, consider following us on social media:

Defense AI Brief AI Brief AI Brief (X)

More from: Defense

08/11
Air and Applied Research Associates Link Fuel Sensors to AI Logistics Platform
08/11
Neros Raises $250 Million to Scale Autonomous Drone Programs
08/11
Vatn Systems and NCSIST Explore Undersea Autonomy for Taiwan Defense
08/11
Inturai Adds DomeCommand Capabilities for Drone Defense
08/03
American Rheinmetall Gets U.S. Army Contract for Autonomous Logistics Vehicles

Subscribe to Defense AI Brief

Your weekly intelligence briefing on the technology shaping modern warfare and national security.

AI Token Webinar

Whitepaper

AI and the Law: Discussion Paper

This discussion paper explores the intersection of artificial intelligence and legal frameworks, addressing potential legal challenges posed by AI's autonomy, adaptiveness, and opacity. It examines issues such as liability gaps, causation, and the potential for granting AI systems legal personality, aiming to foster further discussion on AI's impact on law reform.

Read more

You May Also Like