The Sound of the Battlefield: RADD and the Rise of Acoustic Drone Detection
One of the most consequential shifts in modern warfare is not just the proliferation of drones, but the quieting of their signatures. On the battlefields of Ukraine, fiber optic FPV drones have exposed a growing vulnerability in Western detection architectures. These systems, long reliant on radio frequency sensing and high end radar, are increasingly ineffective against platforms that emit no detectable signal and fly beneath conventional thresholds.
This is the gap that Reconnaissance and Detection Device Company (RADD) is aiming to fill. Emerging from stealth as a TurbineOne spinout, the company is building a new category of drone detection centered on acoustic sensing. Its premise is simple but difficult to ignore. As adversaries eliminate electronic signatures, sound remains one of the last unavoidable emissions. Unlike RF signals, it cannot be switched off. Unlike radar returns, it cannot easily be minimized without sacrificing performance. In an environment where detection is becoming optional for the attacker, acoustic sensing offers a rare constant.
RADD’s leadership reflects a blend of operational experience and defense technology development. CEO Court Vanzant, a former TurbineOne Chief Growth Officer and Army Reserve officer, partnered with Dave Lucas, a veteran Special Forces officer with nearly three decades of service. The company’s flagship system, GLADIUS, builds on an earlier TurbineOne prototype that was set aside as the company focused on software. Rather than letting the concept fade, Vanzant saw an opportunity to refine and operationalize it.
The result is a soldier borne acoustic detection system designed to operate at the tactical edge. GLADIUS consists of two components. The first is a lightweight, dismounted sensor carried by individual operators. The second is a command node that aggregates detections and integrates them into a broader command and control architecture. Together, they form a distributed sensing network capable of identifying aerial threats and relaying them across a unit in real time.
What distinguishes GLADIUS is not just its form factor, but its approach to detection. The system relies on machine learning models trained to recognize the acoustic signatures of drone propulsion systems, particularly rotor blades. These signatures are difficult to mask and vary in predictable ways across drone types. By focusing on waveform recognition rather than emissions or reflections, RADD is targeting a layer of the problem that has remained largely underexploited.
The operational logic is already validated by the battlefield. Fiber optic guided drones, increasingly visible in Ukraine, bypass RF detection entirely. Their control signals travel through physical cables, rendering electronic surveillance irrelevant. At the same time, their low altitude flight profiles reduce radar visibility. In such an environment, acoustic detection may not be an alternative. It may be the only viable option.
Early testing suggests the concept has traction. During a recent Army Transformation in Contact exercise in New Mexico, GLADIUS demonstrated the ability to detect a range of drone types, including quadcopters and multi rotor systems, at distances approaching 500 meters. Evaluators reported strong interest in rapid deployment, indicating that the demand signal for such capability is already present within operational units.
The system itself is designed with scalability in mind. The current prototype is roughly the size of a tissue box, but the company is working toward a form factor comparable to a standard personal radio. Weight targets are equally ambitious, with the goal of keeping the device lighter than a typical rifle magazine while maintaining a battery life measured in days rather than hours. These constraints are not incidental. They reflect a broader shift toward distributed, soldier level sensing rather than reliance on centralized platforms.
RADD is now moving toward low rate initial production while building partnerships to integrate its system into existing command and control environments. The ambition extends beyond a single product. The company is positioning itself within a larger system of systems approach, where acoustic sensing becomes one layer in a multi modal detection architecture.
The significance of this shift should not be understated. For decades, advances in sensing have been driven by more powerful radars and more sensitive electronic surveillance. But the battlefield is adapting. As drones become cheaper, quieter in the electromagnetic spectrum, and more numerous, detection is no longer a question of capability alone. It is a question of economics and resilience.
Acoustic sensing does not replace radar or RF systems. It complements them by covering a gap that is widening with each iteration of drone design. In doing so, it highlights a broader trend. The future of defense technology will not be defined by singular breakthroughs, but by the ability to integrate overlooked signals into coherent and scalable systems. RADD’s emergence is an early indicator of that shift.