by Kris Osborn, President, Center for Military Modernization
Drone swarms can blanket an area with surveillance across a wide envelope with built in redundancy, something which makes them a high threat and very difficult to counter. Drone swarms can also test enemy air defenses or even network to one another in some instances to relay time-sensitive target data. Can they be stopped?
Russian news reports claim the country’s military has pioneered a new kind of “mobile” radar capable of tracking and defending against or “jamming” small drones and possibly even drone swarms.
The TASS News Agency reports that the multifunctional radar can detect small drones in “hovering” mode, meaning as they linger in a more static position to conduct surveillance missions, adding the new technology is particularly impactful in urban areas. It would make sense that such a technology, however mature it is, might prove particularly relevant in urban areas as it could enable dismounted units to “see” over buildings, around corners or into otherwise unreachable areas.
The article does not offer much detail on the technology, and says it was unveiled by Russian weapons maker Rostec at an Army-2023 International Military-Technical Forum. Developers of the radar explain that it is optimally suited for dismounted units, as it weighs only 25 kg and can be transported on foot by mobile soldiers.
“Completed tests demonstrated that the portable radar can be used in conditions of close city development, to protect water areas, by patrol teams, and is able to detect a miniature drone at a distance up to 500 m. Furthermore, the radar “sees” radio transparent targets also, for example, aerostats, which provides for extra protection of secured facilities,” CEO of the plant Andrey Komogortsev said, as quoted in the TASS article.
Although the Russian paper describes the technology as ground-breaking new technology, the ability for ground-mobile radar to track and “jam” drones has existed for many years with militaries around the world, including of course the US. The ability to detect extremely small drones, particularly if dispersed or in groups, is potentially of tactical significance. Extremely small drones, it would seem clear, might easily be missed or wrongly identified by certain ground based radars, one reason why the Russian technology is engineered to reportedly “see” radio transparent targets invisible to certain kinds of imaging.
Additional details of the technology are not available, however it does seem feasible that extremely small drones could be detected despite being difficult for even precise radar to detect as they may appear similar to a bird or even large insect. Should a drone detection technology truly be radio transparent, then it might be difficult to counter or avoid given the RF detection technologies and electro-optical sensors used by most drones.
The actual scope of the drone defense technology seems unclear regarding its ability to identify drones and truly discriminate them from other objects. Jamming a small “swarm” might also be challenging, although there are clearly ways to “area jam” a group of signals with a single, wide-envelope emission. The concept is similar to a proximity fuse munition, as an “area” is covered by blast debris to destroy multiple targets or, in the case of a jammer, an area is “blanketed” with a wide electromagnetic jamming signal.
The US Army, for instance, operates a wide range of counter drone radars which scan areas for electromagnetic and visual signals of many kinds with a mind to locating small drones. For example, the Army has been working with Raytheon on efforts to detect small drone swarms with a 360-degree radar called KuRFs; KuRFs is a a rotating counter-drone system designed to detect, identify, integrate with fire control and then essentially “recommend” an optimal shooter, effector or countermeasure for a particular threat. These kinds of systems are increasingly using AI to collect a wide sphere of incoming sensor data, organize it and bounce it off of a seemingly limitless data base to identify historical instances where a specific countermeasure worked, determine geographical and atmospheric variables and also identify other kinds of threat details of relevance to a tactical circumstance. In this respect, an AI system can identify an optimal countermeasure, weapons or effector in a matter of milliseconds to counter an approaching drone threat.
The information in the Russian TASS article is quite limited, so there seem to be many unanswered questions regarding methods of detection, precision when it comes to identifying small drones otherwise difficult to find and deploying any electronic countermeasures.
Osborn previously served at the Pentagon as a Highly Qualified Expert with the Office of the Assistant Secretary of the Army—Acquisition, Logistics & Technology. Osborn has also worked as an anchor and on-air military specialist at national TV networks. He has appeared as a guest military expert on Fox News, MSNBC, The Military Channel, and The History Channel. He also has a Masters Degree in Comparative Literature from Columbia University.
