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Navy Develops Autonomous System for UAS Tracking

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Scientific and technical personnel from Naval Surface Warfare Center Panama City Division have created technology designed to identify and track unmanned aerial systems autonomously.

The autonomous UAS detection system, known as the Threat Tracker, uses sensors, 3D radars, machine learning algorithms and unique features to function, Naval Sea Systems Command said Sunday.

Threat Tracker works to spot and classify enemy UAS operating on both land and sea domains. The user may choose the command and control system that receives the tracker's information.

“What makes the Threat Tracker unique is that it incorporates machine learning algorithms to autonomously process radar detections, analyze thermal images to assist in video-based tracking, and classify tracked targets to determine if the object is a UAS,” said Marvin Peardon, Threat Tracker program manager at NSWC PCD.

The detection tool also features a Gyro-stabilized Marine Platform that addresses the issue of imagery distortion.

“The Gyro-stabilized Marine Platform will prevent the imagery from being distorted and possibly misclassified," said Jeremy Johnson, systems manager for the effort.

Both Johnson and Peardon want to pursue operational testing within the year.