DroneWatch AI: Building a Multi-Sensor Drone Detection Demonstrator

说明与用途

DroneWatch AI 通过融合多种弱信号源，展示了在不增加硬件的情况下降低误报并提供清晰威胁评估的方法。

问题

Commercial drones threaten critical infrastructure, but specialized counter‑drone hardware is expensive and coverage is sparse. Single sensors produce noisy false alarms that overwhelm operators.

结果

The demonstrator shows that software fusion of existing sensors can reduce false alarms and provide clear threat assessments without additional hardware.

工作流

• Collect live ADS‑B and Remote ID feeds
• Ingest radio‑frequency, acoustic, telemetry, registry, and human reports
• Apply deterministic rules to filter authorised flights
• Use AI layer to explain threat level
• Push scored track to existing command interfaces (ASTM F3411, ADS‑B, ASTERIX, U‑space/UTM, STANAG 4586/4609, Link 16)

证据

The drone-threat signals are simulated. Two public feeds are live and real: ADS‑B air traffic and, since 25 September 2026, network Remote ID

来源

A HIGH assessment requires at least two independent sensors to agree and a contact with no matching authorised flight

来源

It stays strictly defensive: detection and early‑warning only, with any response left to a separate, authorised, human‑in‑the‑loop system

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