From an early point in the Russian war in Ukraine, we’ve seen many unorthodox efforts to try to improve the chances of survival of fighting vehicles. Now, Russian trucks are receiving ‘dazzle paint,’ borrowing the same kind of tactic Russia has used for some of its most important military aircraft, to try to confuse seekers on standoff weaponry that use image-matching capability.
Several images showing the unusually painted Russian trucks have appeared on social media channels in recent days. So far, examples of Ural and KAMAZ heavy-duty truck designs have surfaced. There are at least two distinct patterns so far: a zebra-style application of broadly straight lines, and a more organic, leaf-like, swirling design. In both cases, they extend over most external surfaces, including the wheels and tires. It is not entirely clear if the white paint is applied over a layer of black, or portions of black, or if the white is simply coated over the standard base color of very dark green. It could be a mix of both application concepts, as well.
At first sight, the truck patterns recall the iconic paint scheme that the U.K. Royal Navy pioneered for its warships back in World War I. ‘Dazzle paint’ or ‘dazzle camouflage’ was devised in 1917 by official War Artist Norman Wilkinson, as a means of reducing losses to attacks by German submarines, or U-boats. The geometric patterns work by using highly contrasting color blocks, often heavily featuring black and white, as part of a carefully constructed pattern that breaks up the form of the ship and makes it harder to judge range and perspective.
As you can read about here, this kind of naval camouflage scheme appeared again during World War II, and on several occasions since then.
When first introduced, dazzle paint was intended to trick the human eye, normally looking through a periscope. There was still a benefit to be had in protecting vessels after the introduction of improved rangefinders and radar. For the eye, it made it harder to judge a ship’s course and speed, as well as simply identifying it reliably.
The same basic principle is at work on the dazzle-painted Russian trucks, although now it’s an artificial eye — chiefly using electro-optical and/or infrared cameras — that is supposed to be fooled.
Increasingly, Ukrainian drones are using artificial intelligence (AI) to boost their combat effectiveness. The revolutions that are coming as a result of embedding of AI into lower-end drones is something you can read about in our past feature here. This includes machine vision: a process of the drone learning object recognition, identification, classification, and tracking, as well as providing recommendations for the operator on what to do, provided there is an operator at all and the drone is not running autonomously.
AI-enabled capabilities make lower-end drones more resistant to electronic warfare systems and make it easier for them to be employed in networked swarms. Above all else, they can result in the cutting of the invisible radio frequency tether of constant man-in-the-loop control that in many ways hampers the potential of this class of drones.
The drawback of machine vision that the Russian countermeasure is supposed to exploit is the onboard AI agent’s capacity for learning object recognition. While it may be able to recognize a 6×6 Ural, for example, out of a wide range of potential truck targets, if the appearance of the vehicle is distorted enough, it will not be positively identified, or at least meet the threshold of corroboration that would result in a kinetic act. However, still with many drones that feature AI assistance, a human operator stays in or on the loop for all critical decisions.
This raises the question of how successful the dazzle-painted trucks might be, although the thinking here presumably stresses avoidance of detection during the autonomous target-search phase, rather than the endgame of an engagement. It is also worth noting that these kinds of paint schemes only really have value in areas where they are unlikely to be seen by any Ukrainian human eyes, even remotely via a sensor; after all, they are far more conspicuous than their standard-painted counterparts. It’s also possible that a drone could be taught to specifically hunt these patterns, as nothing else on the battlefield would look like them and they would be confirmed hostile by default.
Overall, paint schemes are another logical, if extemporized response to a growing threat in the Russian rear areas, following the example of the Russian trucks loaded with logs as makeshift armor to protect against kinetic threats in the early phases of the war.
This has been followed by successive counter-drone measures, best exemplified by the increasingly complicated ‘cope cages,’ ‘turtle tanks,’ nets, and arrays of spikes that have appeared on a range of vehicles on both sides of the war.
Perhaps most apposite, however, is the example of Russian bombers and strike aircraft being covered with disused tires, something that first appeared in around August 2023. TWZ was first to postulate that these were most likely intended to confuse the seekers on Ukrainian cruise missiles and drones that use image-matching capability. This was subsequently confirmed by a senior U.S. military technologist.
A “sort of classic unclassified example that exists is like a picture of a plane from the top, and you’re looking for a plane, and then if you put tires on top of the wings, all of a sudden, a lot of computer vision models have difficulty identifying that that’s a plane,” Schuyler Moore, U.S. Central Command’s first-ever Chief Technology Officer, explained in September 2024.
Moore said this as part of a larger discussion about AI models and data sets.
It’s also worth noting that Russian combat ships based in Crimea also received unique shading to break up their silhouettes for the same purpose during this period.
As TWZ has explored in detail in the past, AI is now pushing drones toward a major new evolution, if not a revolution in capabilities.
As well as the possibility of operating in large groups or fully networked swarms, it means long-range one-way attack drones can conduct dynamic targeting deep in contested territory. Trucks, for example, can be hunted and struck far behind the front lines, where once they were safe and where air defenses are sparse.
This is a scenario we have set out in the past, too:
“Waves of similar drones could be sent to their own individual geographical ‘kill boxes,’ or defined areas of engagement. Collectively, they could put enemy targets at risk over a huge area persistently without ‘doubling up’ and attacking the same target twice. Using machine learning/AI and associated hardware, they could not just identify targets of interest, but also differentiate moving from still targets, to ensure they are indeed active (not destroyed or already damaged) vehicles. Meanwhile, they can be set to engage other target types, such as surface-to-air missile systems or other high-priority targets, regardless of whether they are static or not. Even troop movements on the ground could potentially be recognized and attacked. All the parameters as to what the drone can engage, and where it can do so, can be defined and tailored to each mission before launch.”
It is also worth noting that different types of sensors will be affected to different degrees by passive countermeasures like complex paint jobs. While electro-optical sensors may have issues with the patterns, infrared may not, especially at longer wavelengths.
TWZ has previously highlighted how AI algorithms can be rapidly trained in a digital environment, as well as incorporate data collected from actual real-world employment, to improve their ability to spot, categorize, and engage targets. It is, however, unclear how hard it would be to overcome infinite dazzle patterns. It could, as Schuyler Moore observed, lead to software programmers spending inordinate amounts of time on computer vision with very little to gain, once a new pattern arrived.
While it remains to be seen how effective the dazzle-painted trucks might be, they are another sign of drones, especially AI-enabled ones, being one of the key drivers of innovation on the modern battlefield.
Contact the author: thomas@thewarzone.com