Sonic ScaN

Acoustic Drone Detection

Modern drone threats, including low-flying FPV kamikaze drones, often evade traditional radar and RF sensors. Netline’s SonicScan adds a critical acoustic layer of protection, harnessing advanced microphone arrays and AIpowered classification to deliver realtime detection where other technologies fall short.

The system is designed for Airports, borders, critical infrastructure, and defense operations requiring reliable early warning and expanded aerial threat coverage.

Advanced Acoustic Detection for Modern Threats

SonicScan combines AI-powered acoustic sensing with a scalable, modular architecture for uninterrupted monitoring of airports, borders, and critical sites.
Designed for flexibility, it can operate as a standalone solution or integrate with other sensors to enhance accuracy and situational awareness.

Coverage, microphone sensitivity, and detection range can be expanded by adding arrays, with seamless integration across deployments. The system supports both mobile use on vehicles and fixed installations such as perimeters, prisons, and critical infrastructure.


Key Features

  • Next generation sensing – Omnidirectional or beamforming microphone arrays capture acoustic signatures from all directions.
  • AI powered classification – Accurately distinguishes drones from ambient noise in real time.
  • Networked coverage – Connect sensors via Ethernet, WiFi, fiber, or cellular for seamless, continuous monitoring of large areas.
  • Versatile deployment – Mount on existing infrastructure, vehicles, or remote sites to match any operational need.
  • Fully passive operation – Lowprofile, camouflaged sensors remain undetectable.
  • Standalone or multisensor operation – Integrate with radars, EO/IR, and other detection technologies to enhance situational awareness.

Alerts & Analytics:

  • Automated Real-Time Alerts: Instant notifications by SMS, email, or dashboard with detection confidence and location (where available).
  • Audio Streaming for Manual Review: Realtime and recorded audio streaming for verification and analysis.

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