Counter-UAS in the Real World: From Sensor Fusion to 90% Intercept Rates

As small, low-slow drones become cheaper, quieter, and more autonomous, the counter-UAS conversation has shifted from theory to operational reality. Critical infrastructure sites, defense facilities, and public venues are no longer asking whether they need layered airspace protection, but how to deploy it in cluttered, regulation-constrained environments without overwhelming operators with false alarms.

The competitive counter-UAS landscape includes leading players such as Anduril, Dedrone, DroneShield, Rafael, Fortem Technologies, Saab, and other defense and dual-use airspace security providers.

In written responses attributed to Adam Robertson, co-founder and chief technology officer of Fortem Technologies, the company outlined how real-world deployments are balancing detection probability, false positive reduction, and lawful mitigation.

We also reached out to Saab following the unveiling of its Nimbrix Counter-UAS missile at DSEI 2025, requesting comment on the specific operational gaps the system is designed to address compared to existing solutions, early customer feedback, and evolving demand across military and critical infrastructure markets. Lisa Modin, Media Relations Manager at Saab Press Centre, declined to comment.

Layered Detection in Cluttered Airspace

Urban and mixed-perimeter environments present a unique detection challenge. RF sensors can identify drones that are actively transmitting, but waypoint-programmed “RF-dark” drones evade that layer entirely. EO/IR sensors provide visual confirmation, yet degrade in rain, fog, or snow. Radar performs better in adverse weather but must contend with birds, wind-blown debris, and legally operated drones.

Robertson argues that no single sensor type is sufficient. “A multi-sensor layered approach is the key to a robust solution for detecting low, slow, and small drones,” he wrote. The practical solution, according to Fortem, lies in machine-learning-driven sensor fusion that correlates radar signatures, RF emissions, and camera-based classification into a single operational picture.

Rather than relying on threshold triggers from one modality, the system compares and validates detections across sensors in real time. On-radar classification reduces clutter-induced alerts, while camera-based confirmation helps discriminate between birds and drones. RF detection adds context where available, particularly for identifying operators in non-malicious incursions.

In dense RF environments where legitimate drones are present, this correlation layer becomes critical. Without it, false positives can escalate rapidly, degrading operator confidence and response speed.

Adam Robertson, co-founder and chief technology officer of Fortem Technologies

From Detection to Neutralization

Integration into existing command and control infrastructure remains one of the more complex phases of deployment. According to Robertson, Fortem begins with a structured site survey process that evaluates likely threat vectors, line-of-sight coverage, electromagnetic conditions, and power and communications access.

Satellite imagery analysis precedes on-site assessment, followed by detailed calibration during installation and training. The objective is not simply sensor placement, but architectural alignment with base workflows and escalation procedures.

Training, Robertson notes, includes classroom instruction, demonstrations, and hands-on operation until the client can independently run the system. Some customers choose fully managed operation; others opt for train-the-trainer models.

This structured approach addresses a core operational requirement: reliable handoff from detection to mitigation. In counter-UAS scenarios, seconds matter. Sensor data must flow into command systems with minimal latency, and mitigation decisions must be traceable and compliant with local regulations.

Measuring Performance Under Legal Constraints

Post-event metrics in counter-UAS are shaped not only by technical capability but also by legal authority. In many jurisdictions, particularly in domestic U.S. airspace, mitigation options such as RF jamming or takeover have historically been constrained by laws related to wiretapping, GPS interference, and property seizure.

Robertson notes that this regulatory landscape shifted in December 2025 with passage of the SAFER SKIES Act as part of the National Defense Authorization Act. The law expanded counter-UAS authority to properly trained state, local, tribal, and territorial agencies under defined reporting and oversight requirements. Agencies must now report mitigation actions within 48 hours, detailing location, timing, threat description, capability used, and operational effects.

In practical terms, many real-world incidents are resolved before kinetic or electronic mitigation becomes necessary. “By far, most active threats involve unauthorized or uninformed drone operators flying where they shouldn’t,” Robertson wrote. In those cases, RF detection combined with human intelligence identifies the operator, and the incident is resolved through compliance rather than force.

Where physical mitigation is required, Fortem deploys its DroneHunter net-capture interceptor system. Across thousands of testing scenarios and operational encounters, Robertson states that the system has matured to a success rate exceeding 90%, with consumer quadcopters generally easier to defeat than faster, more agile platforms.

Primary metrics in these environments include probability of detection, probability of mitigation, and response time within an escalation-of-force framework. Swarm scenarios and high-speed drones remain more challenging, but layered detection and autonomous guidance have improved reliability.

The Operational Reality

The counter-UAS domain is no longer defined solely by hardware specifications. It is defined by integration discipline, regulatory compliance, and the ability to operate continuously in complex environments without overwhelming human operators.

Layered sensor fusion reduces false alarms. Structured deployment processes minimize blind spots. Expanded mitigation authority clarifies response frameworks. And intercept platforms are moving from experimental to operational maturity.

As drone capabilities continue to evolve, so too must the systems designed to counter them. The data suggests that layered architectures combining radar, RF, EO/IR, and autonomous interceptors are moving from pilot programs into sustained field deployments—where performance is measured not in lab benchmarks, but in real airspace under real constraints.