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Latest in counter-drone technology help protect critical infrastructure

Latest in counter-drone technology help protect critical infrastructure
The latest developments in counter-drone technology are helping critical infrastructure operators fight against the threat of UAVs.
As drone technology gets more advanced, so too must counter-drone — also called anti-drone or counter unmanned aerial system (C-UAS) — technology. From the most basic level, there are a few things that every counter-drone solution must be able to do effectively.

According to Dave Preece, Chief Data Officer and VP of Marketing at Fortem Technolgies, a counter-drone solution must be able to see/detect, track, classify, identify and assess all drones in the protected airspace. It must also be able to integrate with existing security systems and sensors, as well as be able to ingest third-party data sets, such as those provided by unmanned traffic management (UTM), automatic dependent surveillance — broadcast (ADS-B) and Remote ID.

“A viable counter-drone system must be able to protect the existing security above and beyond its fence lines and map to rules of engagement and escalation of force protocols that are in place,” Preece said.

On the market today there are three basic sensors available for drone detection: radar, radio frequency (RF) monitoring and optical sensors, each of which have their own set of limitations. Thorsten Chmielus, CEO of Aaronia opined that radar technology is inefficient when considering drone detection due to the size of drones and limitations in the radars, such as coverage, opening angles and range.
Thorsten Chmielus, CEO, Aaronia

“The solution further becomes expensive when we consider the need for visual verification due to potential false alarms from birds, leaves falling from trees, sandstorms and more. Because of these problems radar can’t be used as a so-called main sensor,” Chmielus said.

On the other hand, RF monitoring presents several benefits including greater range of detection and simultaneous detection, verification and classification. However, for the most part these systems only offer simple direction finding, or even worse only RF monitoring of common frequency bands, which is of no use since today’s latest generation of drones can operate at any frequency band, Chmielus explained.

Preece pointed out that the large majority of anti-drone technology today relies on radio frequency. “RF solutions are OK for clueless and careless drone operators who are using a drone’s remote control device to fly the drone. In these cases RF solutions can locate a rogue drone and then interrupt the signal by taking it over or jamming it. They can also locate the drone operator,” he said.

Unfortunately, now that criminal and terrorist drone operators know they can be detected, they do not employ a remote control. In fact, according to Preece, criminal operators can fly most drones without detectable RF (RF-silent drones) by using easy-to-use free downloadable software.

A report by Frost & Sullivan pointed to “disruptive transformations in the [C-UAS] market” in the form of artificial intelligence (AI) algorithms that can automate the detection, identification, locating and tracking of drones with minimal false alarms, and directed energy weapons that can mitigate multiple drones quickly and/or simultaneously.

To capitalize on the future of the C-UAS market, Frost & Sullivan recommends that companies develop as-a-service revenue streams with effective systems that are easily transportable; build C-UAS that can detect, locate and track drones no matter what their configuration or mission; and integrate advanced AI into C-UAS to automate as much of the process as possible.

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