Experts believe that an effective approach to countering swarms of drones may require a multi-layered defense system, incorporating electronic jamming, surface-to-air missiles, and lasers.
The People's Liberation Army of China (PLA) recently tested its capabilities against drone swarms, achieving only a 40 percent success rate when countering a swarm of 11-12 drones.
Drones continue to transform the dynamics of the modern battlefield. Small unmanned aerial vehicles (UAVs) are being effectively deployed against main battle tanks (MBTs), convoys, and even frontline positions of the enemy. Even a single first-person view (FPV) drone can be difficult to counter, and so-called "swarms" of drones can quickly overwhelm adversaries.
"Swarm tactics surpass individually controlled drones due to the communication between drones, allowing information gathered by one drone's sensors to be transmitted directly to the entire group and adjust their behavior without additional input from operators or commanders," write Josh Curtis and Anthony De Luca-Baratta for The National Interest.
The U.S. Armed Forces are exploring options to counter such threats, but their successes have been limited. The good news is that the same is true for China. The PLA recently conducted an operation to combat a swarm of drones, managing to counter only 40% of it.
Chinese state media reported earlier last month that during recent exercises, the PLA tested its capabilities against drone swarms. Reports indicate that the swarm consisted of only 11-12 commercial-type drones. The task of the 77th Group Army of the PLA was to destroy the drones, utilizing two types of tracked self-propelled anti-aircraft guns.
The international military analysis company Janes reports that it analyzed video footage and "found that initially six Type 95 self-propelled anti-aircraft guns (also known as PGZ-95) engaged the UAVs. Three 35mm PGZ-09 (Type 07) anti-aircraft guns also formed the initial response of the PLA to the UAVs."
According to Janes, "PGZ-95s are equipped with 25mm Type 87 guns featuring a fire control system that includes an electro-optical complex mounted in the front of the turret. The complex consists of a tracking television camera with a range of 6 km, an infrared tracking camera with a range of 5 km, and a laser rangefinder (LRF) with a range of 500-5500 m. All of this assists in calculating data for weapon targeting."
The anti-aircraft units achieved only 40% hit accuracy, which is significantly less effective than the PLA would prefer—and it should be noted that this was only against a dozen drones. If the swarm had consisted of several dozen or possibly hundreds of UAVs, it would imply that a substantial percentage of them would breach defenses.
"Firing at drone swarms remains quite challenging due to their speed and small size, as well as their ability to change flight trajectories, making it easy for gunners to lose track of their targets," CCTV reported Duan Xiaolong from an unnamed regiment of the PLA's 77th Group Army, states Interesting Engineering.
Air defense systems designed to counter manned aircraft and missiles are still effective against individual drones, but the issue lies in their cost. Surface-to-air missiles, which can cost hundreds of thousands or even millions of dollars, are simply not suitable for countering drones.
Countering drone swarms will require a multi-layered defense system that includes electronic jamming systems, surface-to-air missiles, close-in weapon systems (CIWS), directed energy weapons (DEW), and lasers. Even this may not be sufficient to stop a large swarm of drones. However, this is a challenge faced not only by the American military.
Peter Suciu is a journalist from Michigan. Throughout his two-decade journalism career, he has contributed to over forty magazines, newspapers, and websites, publishing more than 3,200 articles. He regularly writes about military technology, the history of firearms, cybersecurity, politics, and international affairs. Peter is also a contributor to Forbes and Clearance Jobs. You can follow him on Twitter: @PeterSuciu. Contact the author via email: [email protected].