Dedrone DedroneRF
Dedrone DedroneRF is a multi-band RF sensor designed for passive detection and classification of drones through analysis of radio frequency communications and signals.
System Overview
What It Is
DedroneRF is a passive RF sensor that detects and classifies drones by analyzing their radio frequency emissions. Part of the Dedrone ecosystem, it feeds detection data into the DedroneTracker command-and-control platform for integrated airspace awareness.
How It Works
The sensor continuously monitors radio frequencies across multiple bands commonly used by drone control links, video downlinks, and telemetry. When a signal matching known drone protocols is detected, AI-powered algorithms classify the drone type and estimate its position. The data is fused with inputs from other sensors (radar, cameras, acoustic) in the DedroneTracker platform.
Primary Capability
Passive RF-based drone detection and classification for airspace security.
Overview
Dedrone DedroneRF is a specialized RF sensor designed to passively detect and classify unmanned aircraft by analyzing their radio frequency emissions. As a core component of the Dedrone airspace security platform, DedroneRF provides the RF sensing layer that, combined with radar, cameras, and acoustic sensors, delivers comprehensive drone detection and tracking capability.
Development History
Dedrone, originally founded in Germany and now headquartered in the United States, developed DedroneRF as part of its mission to secure airspace against unauthorized drone activity. The company was one of the first to apply machine learning to drone RF signal classification, building an extensive library of drone communication signatures. The sensor has been adopted by US federal agencies, military installations, airports, and critical infrastructure operators worldwide.
Operational Concept
DedroneRF sensors are deployed around a protected area, either as standalone units or integrated into a multi-sensor network managed by the DedroneTracker platform. Each sensor passively scans the RF spectrum, using AI algorithms to identify signals associated with drone control links, video feeds, and telemetry. Classified detections are pushed to the central platform where they are fused with data from other sensor types to provide a comprehensive airspace picture. The system can automatically trigger alerts and cue cameras for visual confirmation.
Future Development
Dedrone is investing in advanced signal processing to detect drones using encrypted, frequency-hopping, and custom communication protocols. The company is also expanding its sensor line with improved range and sensitivity, and deepening integration with effector systems for a complete detect-to-defeat capability.
Technical Specifications
- Multi-band RF scanning
- Detection range: up to 5 km
- Passive operation
- AI-powered classification engine
- Drone protocol library: 300+ types
- Weatherproof outdoor housing
Range
Up to 5 km
Compatible Platforms
Deployed By
Key Features
- AI-driven classification for high accuracy
- Extensive protocol library covering 300+ drone types
- Seamless integration with DedroneTracker C2
- Multi-sensor fusion capable
- Over-the-air library updates
Advantages
- Very high classification accuracy
- No emissions or spectrum authorization required
- Scalable from single sensor to large networks
- Low total cost of ownership
Limitations
- Cannot detect RF-silent drones
- Detection range varies with environment
- Sensor only — no defeat capability
- Performance affected by RF congestion in urban areas