Counter drone defense through computer vision and machine learning

Enforce Field uses full motion video (FMV) to detect, classify, and track drones to protect our military, critical infrastructure, and air traveling public.

Enforce Field

The proliferation of small unmanned aerial systems (sUAS), commercially known as drones, is an asymmetric security and safety issue. Enforce Field employs computer vision machine intelligenceintegrated with full motion video sensors to detect, identify, and track UAS aircraft for unprecedented situational awareness for military and civilian aviation personnel.

  • Tactical - Lightweight FMV passive sensor allows C-UAS operations in non-radar (EMCON) environments
  • Low Bandwidth - 100-200 kbps per video source (30 fps)
  • Diverse Operations - Installation on stationary and mobile platforms (buildings, towers, vehicles, drones, aircraft)
  • Disparate Sources - Compatible with camera systems employing full range of optical characteristics, pixel density, and spectrum (visual, EO/IR, full)
  • Target Agnostic - Detect, classify, and track unmanned drone and piloted aircraft allowing complete situational awareness of operational airspace.


Jamie Ter Beest
Project Lead
Doug Grant
Business Development
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  • Near real-time PNT (Position Navigation and Timing) data (course, speed, altitude, range, bearing)
  • Predictive and empirical machine learning for track classification and detection confidence level
  • IFF capability for user-defined drone/aircraft classification and response
  • JSON data feed for third party systems (ATAK, GIS, AR/VR)
  • Night operations capability with appropriate optics hardware
  • Timestamp and positioning allow local or remote server operation