For years, radio frequency (RF) detection has been the backbone of counter-drone operations worldwide. Military bases, airports, and critical infrastructure have invested billions in systems designed to spot unauthorized drones by listening for their telemetry signals and communication links.

But according to new data provided to The Drone Girl from Dedrone by Axon, that foundation is crumbling beneath our feet.

RF detection is not what it was

In September 2025, Dedrone by Axon shared some key insights into its operational datasets from 2024 and 2025 across Europe, the Middle East, and Asia in a report titled The State of Airspace Defense Today and What’s Next.

Dedrone by Axon builds products that can monitor airspace and detect unwanted drones in there. The airspace security company can then mitigate those threats using its technology.

And its latest report reveals an interesting trend: while over 80% of current drone detections still rely on RF systems, a growing number of drone operations are deliberately avoiding radio signals altogether. This shift toward “RF-silent” flights represents is certainly a compelling tactical evolution. For defense teams, it’s a threat to its detection infrastructure.

Just look to the war in Ukraine. Ukraine’s recent military operations have demonstrated how pre-programmed drones can be deployed without any radio communication, navigating to targets using GPS coordinates, inertial navigation or even visual recognition systems. When these drones go completely dark, traditional RF sensors become as useful as listening for telegraph signals in the smartphone age.

How drone pilots avoid RF detection

Modern drone operators have multiple ways to avoid RF detection, and the technology is becoming more accessible. Examples include:

Fiber-Optic tethers: These provide a physical connection between operator and drone that’s completely immune to jamming and invisible to RF sensors. While they limit range, they’re good for reconnaissance missions or short-range attacks.

Pre-programmed navigation: Drones can be loaded with flight paths and targets before takeoff, eliminating the need for real-time communication. Advanced versions use SLAM (Simultaneous Localization and Mapping) technology to navigate visually, like a drone version of a self-driving car.

Autonomous swarms: Using AI coordination, multiple drones can operate as a unit with minimal or no radio communication, sharing information through mesh networks or operating on predetermined algorithms.

Signal Spoofing: Rather than going silent, some operators are feeding false information to RF detection systems, making malicious drones appear as friendly aircraft or civilian traffic.

Fly at night: Dedrone’s report found that 37.5% of all drone detections in 2025 occurred during night operations. That’s a clear indication that operators are exploiting reduced visibility to avoid visual detection while simultaneously working to defeat RF sensors.

This tactical shift makes sense from an operational perspective. If you can fly without radio signals during low-visibility conditions, you’ve eliminated two of the three primary detection methods (RF and visual) that most defense systems rely on. Only radar and acoustic sensors remain viable, and both have significant limitations against small, slow-moving targets.

The power of DIY drones against drone detection systems

Dedrone’s data shows a 4.3x increase in DIY drone detections in 2025 compared to 2024. These custom-built platforms often operate on modified or entirely proprietary communication protocols that don’t match the RF signatures that detection systems are trained to recognize.

Unlike commercial drones from major manufacturers like DJI, which use standardized communication protocols, DIY builds can employ anything from modified RC car controllers to completely custom radio systems — or no radio at all. This diversity makes it nearly impossible for RF detection systems to maintain comprehensive signature libraries.

What now? These sensors are better

The death of RF-centric detection requires a complete rethinking of sensor architecture, Dedrone says. That could include:

Radar integration: Modern radar systems are becoming more sophisticated at distinguishing drone-sized targets from environmental clutter, but they need to be paired with other sensors for reliable identification.

Acoustic detection: Drones still make noise, and acoustic sensors can identify the unique sound signatures of different rotor configurations. However, even this is tricky as advances in electric propulsion are making drones quieter.

Visual and thermal imaging: AI-powered cameras can identify drones visually, even at night using thermal signatures. But they require clear lines of sight and can be defeated by weather or camouflage.

What to expect going forward

Most drone detections systems are designed around the assumption that hostile or foreign drones would need to communicate with their operators. Remove that assumption, and the entire detection architecture becomes unreliable.

“The drone threat is evolving faster than most defenses can respond,” said Aaditya Devarakonda, CEO of Dedrone by Axon.

And the challenge will likely only compound as RF detection continues to decline in effectiveness. As autonomous navigation improves and becomes more accessible, more operators will adopt RF-silent tactics.

Organizations that have invested heavily in radio-based counter-drone systems will likely need to spend money to upgraded or replace their infrastructure with multi-sensor platforms. For its part, Dedrone by Axon, which released the data, makes such platforms.

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