Detection Methods

Detection Methods

Overview of the primary sensing modalities used to detect drones, with comparative analysis for the critical infrastructure use case (fixed-site protection, drone-vs-bird discrimination, RF-dark threats).

Entries

Entries

  • Acoustic Detection — Acoustic drone detection using microphone arrays and machine learning analysis of motor and rotor noise signatures — detects RF-dark and fiber-optic drones; limited range; strong bird discrimination.
  • FAA Remote ID Monitoring — Reception and decoding of FAA/ASTM F3411 Remote ID broadcasts — the fastest path to identifying compliant US drones, but entirely dependent on the drone's voluntary cooperation. See RF Direction Finding for detection that doesn't require it.
  • Micro-Doppler Radar — Micro-Doppler radar signatures produced by rotating drone blades enable reliable drone-vs-bird discrimination and detection of hovering/slow targets that evade conventional Doppler radar.
  • Multi-Sensor Fusion — Combining radar, RF, acoustic, and optical/thermal sensors for reliable drone detection — each modality covers the others' blind spots; fusion is required to detect the full threat spectrum including RF-dark drones.
  • Optical / Thermal Detection — Electro-optical and infrared (EO/IR) camera systems for drone detection — the only modality effective against fiber-optic tethered drones in a passive sensor role; requires AI classification to discriminate drones from birds.
  • RF Direction Finding (Non-Cooperative) — Passive RF detection and triangulation of drone control-link and video-downlink emissions — locates any RF-emitting drone regardless of whether it broadcasts Remote ID or cooperates in any way.
  • Swarm Detection — State of the art in detecting coordinated multi-drone swarm attacks — what makes swarms uniquely hard to detect, which detection methods scale, and the current commercial and research approaches.