Making Enemy Drones Easier To Detect With Smart Tag Technology

In the early hours of July 19, residents of Tel Aviv were awakened by the tremendous boom of an unmanned aircraft, laden with explosives, smashing into a residential building and killing a civilian as he slept in his bed.

The drone was one of a small swarm sent by the Iranian-backed Houthi terror group in Yemen, and had escaped Israel’s multi-layered air defense systems due to human error caused by its lack of a discernable signature. 

Failing to identify the danger posed by the drone, the Israel Defense Forces later said, no sirens were activated to warn locals of the incoming attack and tell them to seek shelter. 

The incident revealed a potentially worrisome gap in the legendary Israeli air defenses, as the small size of the drone made it hard to detect with radar, which bounces signals off a targeted object to identify it, or with the cameras and transponders that are also used.  

Israel has been targeted by hundreds of these small yet extremely destructive drones since the start of its war against the Hamas terrorist organization in Gaza, which was triggered by the mass terror attack on October 7 that saw 1,200 people brutally murdered in southern Israel and hundreds more abducted and held hostage. 

The drone attacks have come primarily from the Iranian-backed Hezbollah terror group in Lebanon and caused major destruction in parts of northern Israel, although some have also been sent by the Houthis in Yemen. 

Seeking a solution to this problem, researchers at Tel Aviv University’s Faculty of Engineering have developed an electromagnetic tag that is placed on the wings of hostile unmanned aerial vehicles (UAVs), making the aircraft easier to identify and track. 

The research team was led by PhD students Omer Tzidki and Dmytro Vovchuk at the lab of Prof. Pavel Ginzburg, which specializes in developing new radar and wireless communication technologies to address current and future challenges.

“Contrary to traditional airborne targets, small drones and copters pose a significant problem for radar systems due to their relatively small radar cross-sections,” the research team wrote in its abstract paper.  

“Small UAVs pose significant security issues, as has been proven in many unfortunate cases worldwide and the number of safety issues will continue to grow,” the team warned. 

“Due to their low cost and unlicensed accessibility, small drones can be used by unauthorized users to carry dangerous items, spot classified sites, interfere with air traffic, and for other undesired purposes.” 

The tag works by daubing the drone with an electromagnetic “sticker” that is recognized by radar. The radar uses AI algorithms to sense what the team calls the drone’s identity card, presented by the increased electromagnetic signal emitted by the stickers. 

The algorithm then can decipher whether the drone is friendly or hostile, allowing the security forces to respond accordingly, and can do so even in the adverse conditions that had previously proven to be a challenge.   

“We are glad to suggest a solution so that it is not vulnerable,” Tzidki tells NoCamels. “The project has a vital meaning, particularly in these days.”

The researchers say the smart tagging approach works even with challenges such as urban environments, poor visibility, poor weather conditions, low-altitude flights and the presence of additional air traffic – all of which make it harder to identify the specific signal of the drone. 

Experiments of the system were initially carried out in sterile lab conditions, and later in an external setting that simulated real-world scenarios. 

According to Tzidki, optimal results were created by the combination of electromagnetic techniques, AI algorithms and innovative radar technology.  Now more than ever, such technology is “critical for protecting the lives of soldiers and civilians,” he said. 

Identifying the drones is especially critical when there is no direct line of sight, he said, making the use of radar all the more important. 

Ginzburg also hailed the research as a simple solution to a complex problem, calling it a “significant” achievement.  

“The simplest things often work best,” Ginzburg said. 

“This project leverages fundamental physical principles to reliably and accurately classify drones. The process of identifying any drone using radar is quite complex, so achieving the capability to identify specific drones is a significant accomplishment of which we are very proud.”

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