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The game-changing technology, based on a network of passive rooftop sensors that capture electro-optical and infrared data (EO/IR), continuously scans the sky – at a much lower cost than RADAR.
In the future, if the Drone Net’s all-sky camera and connected acoustic network detect a small unmanned aerial system (sUAS) without a flight plan, or off its flight plan, the technology will kick into gear. Specifically, the all-sky camera will cue an EO/IR camera to slew and track the sUAS with high-resolution visible and infrared imaging until the non-compliant sUAS leaves the area monitored by Drone Net – encompassing about 1 square kilometer.
“When the all-sky and acoustic system detects something moving,” said Siewert, an assistant professor of electrical, computer and software engineering, “it activates automatically, sort of like lizard-brain intelligence. It sends a message to begin electro-optical and infrared sensing by tilting and panning the camera to redetect the sUAS in a narrow field of view. The EO/IR sensing is controlled by machine intelligence, so that it will re-detect and track, supporting the identification of drones by ground-based computing systems.”
Ultimately, the goal of the research is to help law enforcement distinguish between responsible drone operators and possibly hostile ones by creating a database of drone “fingerprints.” The researchers, working on Embry-Riddle’s Prescott, Ariz., campus, will compare and validate data captured by the Drone Net with information from many other types of passive and active sensors.
Embry-Riddle Eagle Matthew Demi Vis, now an avionics engineer at the Jet Propulsion Laboratory, at work with a copy of the Mars Curiosity Rover.
Scanning Shipping Channels and Skies
Undergraduate research by Matthew Demi Vis – a 2017 Embry-Riddle alumnus now working as an avionics engineer with the Jet Propulsion Laboratory – developed foundational technology that helped set the Drone Net project onto the proverbial launch pad, Siewert noted.
Initially, Vis was part of …