Bristol Airport photo

First U.K. Airport Installation for Digital Global Systems Inc’s Drone Threat Management System

In collaboration with deployment partners, Telent and Airpoint International, Digital Global Systems Inc (DGS) has announced a successful trial of its CLEARSKY™ Drone Threat Management system at Bristol Airport, U.K. As part of a three-year commitment DGS will now provide a network capable of providing detection, classification, and location of unauthorized drones and controllers operating in the flight restriction zones.

CLEARSKY™ delivers detection distances with classification and critical location information using machine learning techniques. The system is also able to locate both drone and controller. “As the incident at Gatwick Airport and other airports demonstrate, these capabilities would have been essential in helping security personnel locate the perpetrators,” says Fernando Murias, Chairman and CEO of DGS. “Additionally, CLEARSKY™ is designed to operate in chaotic and noisy RF environments, including airports and sports stadiums.” 

DGS performs detailed site surveys of the target deployment and adapts the solution for local conditions. The system can also be integrated with third-party systems through standard JSON messaging. Long-range cameras, radar, acoustics, and multi-sensor visualization systems can all be used with CLEARSKY™ to create layered security. At Bristol Airport, this was leveraged to integrate the Airpoint International mobile application. Airpoint International allows security personnel and law enforcement outside of the control room to track the drone and the pilot location on a mobile application.

Software options are available to support detection of any anomalous signal in the RF environment, including wireless jammers, unauthorized 2-way radios, a streaming video surveillance camera, or unknown/new drone protocols. The system’s machine learning engine allows the creation of masks of “normal” RF environments for specific periods in time and compares the current environment to the appropriate mask to detect anomalies.

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