Rapid NATO Counter-Drone System Shines at Bold Machina

If there is one thing modern conflicts have made painfully clear, it is that small drones punch far above their weight. Cheap, fast, and everywhere, they have become the airborne equivalent of mosquitoes with cameras, explosives, or both.

At NATO’s Bold Machina exercise in the Netherlands this September, a rapidly developed counter drone prototype showed that swatting those mosquitoes at sea might finally be getting easier, as reported in a Press Release by the NAVY.

The system, designed and built in a matter of months by a small team from the U.S. Naval Postgraduate School, completed its first real world sea trials aboard a Dutch Navy fast raiding, interception, and special forces craft, better known as a FRISC. Think of a FRISC as a speedboat that skipped leg day and only trained core and attitude.

What makes this counter UAS system special is not brute force. It is subtle. No loud radars shouting into the void. No emissions screaming “here I am.” Instead, it listens, watches, and thinks, quietly, like a chess player who already knows your next move.

A Quiet Hunter for Loud Problems

The system was designed to be fully passive, which is a big deal for special forces operating at sea. If you are trying to stay invisible on open water, lighting up the electromagnetic spectrum is a terrible idea. The NPS team took a different approach, using artificial intelligence to fuse data from multiple independent sensors and turn that into a clear picture of nearby drone threats.

Class 1 drones were the main target. These are the small, easily available drones that are hard to detect and even harder to ignore. Individually they look harmless. In numbers, or with the right payload, they become a nightmare.

By combining acoustic sensors, radio frequency detection, electro optical and infrared cameras, and low probability of intercept radar, the system builds a layered understanding of what is flying nearby. An AI engine running on Nvidia Jetson hardware does the heavy thinking, matching patterns, learning new drone types, and updating its threat library on the fly.

All of this information ends up on a SeaCross navigation display, where operators can see bearing, range, altitude, orientation, and even identify previously unknown drones.

In one test, after encountering the same unknown drone several times, the system learned it, logged it, and flagged it as a threat. That is not science fiction. That is pattern recognition doing its job.

The system ties together sensors and hardware from companies in Australia, Norway, Sweden, and the United States. It is very much a system of systems, held together by software, cooperation, and a shared sense of urgency.

From Pickup Truck to Open Sea

Before heading to the Netherlands, the team tested their prototype at NPS’ Joint Interagency Field Experimentation exercise in California. The environment could not have been more different. Dust, heat, and temperatures well over 100 degrees replaced cold water and sea spray.

To make it work, the team mounted the system on a mast attached to the bed of a pickup truck, effectively creating what they jokingly called a “land boat.” While other teams flew drones around the test area, the counter UAS system tried to detect them, track them, and make sense of the chaos.

Different drones. Different altitudes. Different angles. Sometimes the drones tried to trick microphones or blend into thermal backgrounds. This was exactly the kind of stress testing the system needed. It exposed weaknesses, highlighted strengths, and forced rapid iteration.

Ukrainian officers attending JIFX brought especially valuable insight. Their questions were not theoretical. They came from lived experience, from watching drones adapt day by day in an active warzone. That feedback helped refine how sensors were combined and how the AI interpreted conflicting data.

By the time the team packed up for Bold Machina, the system was still not complete. Some sensors were still arriving. Some integrations had never been tested together. This is normally where projects slow down. At BOMA, it was where things sped up.

Bold Machina and a Real World Test

At sea off the coast of Den Helder, the team finished assembling and integrating the system aboard a Dutch Navy FRISC. Sensors were powered up, connected, and fed into the fusion engine. Then the real test began.

Four types of class 1 drones were launched toward the boat, including standard RF controlled drones, modified RF drones, fiber optic drones, and fully autonomous ones. As the FRISC maneuvered, operators watched the system track the drones in real time on the navigation display.

In some cases, the system did more than just track the drone. It also identified the position of the drone operator. For maritime special forces, that kind of information can be as valuable as the drone detection itself.

Despite the rushed integration and limited sea trial time, the system met the objectives set by NATO SOFCOM. It proved that multiple sensors from different manufacturers could be fused into a single, usable display, quietly, and effectively. That capability did not exist in this form before.

DroneXL’s Take

This story matters even if you never plan to step foot on a NATO fast attack craft. What we are seeing here is the future of counter drone tech, layered sensors, AI driven fusion, rapid development, and constant learning. Today it is protecting special forces at sea. Tomorrow, similar ideas will trickle down into ports, critical infrastructure, and eventually even civilian counter drone solutions.

The biggest lesson is speed. This system went from concept to sea trials in months, not years. In a world where drones evolve faster than software updates, that pace is not impressive, it is necessary. If drones are the mosquitoes of modern warfare, then systems like this are finally starting to look like a working bug spray.

Photo credit: NATO / Deacon Westervelt, U.S. Navy / Dan Linehan