Russian Radar Technologies in EW and Influence Operations
A French engineer’s demonstration of passive and active radar at a 2025 hacker camp reveals how readily available electronics can detect targets by harvesting ambient signals. This experiment underscores a broader trend- passive radar technology, once niche, is now accessible and is being rapidly adopted for covert surveillance and drone defense. Russian defense developers, amid the Ukraine conflict’s drone innovations, have simultaneously unveiled a passive radar system to track “invisible” fiber-optic guided drones without emitting a trace. The convergence of open-source experimentation and state-level deployment of passive radars signals a paradigm shift in electronic warfare – one that makes stealth more elusive and surveillance far more stealthy. The convergence matters now because drones and stealth threats are proliferating, and traditional radars are vulnerable; passive sensing offers a timely countermeasure. The implications extend from protecting troops from otherwise undetectable drones today to a future where battlefields are bristling with “silent” radar sensors, fundamentally altering air defense and reconnaissance. So far, early results show promise (a hacker-sized setup can spot targets, while Russia claims new radars can expose previously untrackable drones), and strategic forecasters expect these low-emission detection methods to proliferate, forcing combatants to rethink both stealth and electronic attack. The outlook suggests an escalating race to use ambient “electromagnetic smog” as a weapon, blurring the line between hobbyist technology and military capability in the realms of surveillance and electronic warfare.
Innovator Demonstrates Low-Cost Passive & Active Radars (Who, What)
In August 2025, radio engineer Jean-Michel Friedt took the stage at the “What Hackers Yearn (WHY) 2025” camp in the Netherlands to showcase a functional radar built from software-defined radio (SDR) receivers and clever signal processing. Friedt’s talk, titled “Passive and active RADAR using Software Defined Radio,” unveiled how dual-channel coherent SDR receivers paired with cross-correlation algorithms can pinpoint a target’s location and movement without the expensive, dedicated hardware of conventional radars (RTL-SDR, 2025). In a passive mode, his setup behaves like a predator lurking in the wild – it remains silent, simply “listening” to pervasive electromagnetic emissions (the radios, TVs, cell towers that bathe our environment) and catching the faint reflections off objects. In active mode, it improvises with “non-cooperative” emitters, such as a Wi-Fi dongle, as a surrogate radar transmitter, which remains far cheaper and more covert than a full-power radar system. All the heavy lifting – from real-time signal acquisition to post-processing – relies on open-source tools, such as GNU Radio for live streaming and GNU Octave or Python for crunching data after the fact (RTL-SDR, 2025). Friedt concluded by demonstrating a DIY form of Synthetic Aperture Radar (SAR), where a small antenna is moved along a rail. This system mimics a much larger antenna, sharpening the resolution in azimuth (the side-to-side dimension) and enabling radar “imaging” of the scene. In essence, he proved that a talented individual with about $1,000 of gear can replicate techniques that were once the jealously guarded domain of defense laboratories.
Key Techniques and Experiments
Friedt’s prototypes illuminated several radar techniques. Passive radar was likened to a hunter exploiting “electromagnetic smog” – the haze of strong broadcast signals already in the air – rather than emitting its signal. Hunter exploitation is the ultimate in covert sensing, as the system does not broadcast, making it difficult for an adversary’s sensors to detect or target it. A coherent dual-channel receiver (two antennas and SDR tuners sharing a standard clock) lies at the heart of the approach. One antenna (the reference channel) locks onto a powerful illuminator signal (for example, a digital TV tower’s transmissions), while the other antenna (surveillance channel) points toward the area of interest to catch any reflections of that broadcast off a moving object. The system teases out the tiny echoed signal from the reference’s direct signal by continuously cross-correlating the reference and surveillance streams. Friedt emphasized that cross-correlation is computationally intensive but vital – it effectively subtracts what was transmitted from what was received, isolating the telltale difference caused by a moving target’s Doppler shift or time delay. He noted that the target range in such passive setups is limited not by transmit power (since external broadcasters give that) but by how well the receiver can isolate the direct versus reflected signals. In other words, the dynamic range and interference rejection of the setup dictate how far the device can see, making good antennas, shielding, and filtering essential, sometimes more so than raw gain.
In active experiments, Friedt’s team used unconventional emitters. For instance, a simple Wi-Fi adapter can be driven to emit a known pseudo-random sequence or wideband noise, acting like a radar “flashlight” that illuminates the scene without resembling a typical radar ping. Such usage might skirt legal transmission limits (indeed, transmitting arbitrary signals can be illegal without a license in many countries), so these experiments tread the line between innovation and regulation. The benefit, however, is control – using a Wi-Fi-based source allowed the team to experiment with pulse radar, FMCW (frequency-modulated continuous wave), and FSCW (frequency-stepped continuous wave) techniques. Those are various radar signal strategies – pulses for straightforward echo timing, FMCW for continuous transmission with frequency chirps (common in automotive radars), and FSCW for hopping between frequencies. Typically, implementing these would require a purpose-built radar transmitter; here, an inexpensive dongle sufficed, demonstrating a “hybrid passive/active” radar where the Wi-Fi acts almost like a random beacon. Notably, because the Wi-Fi signals were inherently noise-like and not designed for radar, it is as if the team co-opted a non-cooperative emitter for radar use – blurring the line between strictly passive and active. It hints at future radars that could opportunistically use ubiquitous emitters (Wi-Fi, Bluetooth, 5G signals) as radar sources, complicating any attempt by an adversary to predict or detect when they are being watched.
The final act, Friedt’s synthetic aperture radar (SAR) demonstration, tied the concepts together with spatial innovation. The system synthesized a much larger antenna aperture over time by physically transporting a small antenna across a track – effectively mounting it on a moving rail platform and sliding it. Each position of the antenna yielded a slightly different viewing angle of the target area; by combining these measurements, the radar achieved finer angular resolution than a single small antenna could. This technique is similar to how airborne SAR works (where an airplane’s motion simulates a large antenna), but here it was implemented on the ground using a Raspberry Pi-controlled mechanical slide. They managed to construct radar images with improved detail in the horizontal direction (azimuth), in addition to the range resolution provided by the signal characteristics. It was a striking finale —a garage-built apparatus performing tricks similar to those of high-end military imaging radars, mapping objects by walking an antenna around.
Real-World Project Highlights
During the talk, Friedt referenced concrete projects to illustrate these principles in action. One setup was a “Ground SAR” scenario using an Ettus Research USRP B210 SDR (a high-quality two-channel radio), a Raspberry Pi 4 for control and data handling, and a Wi-Fi Alfa AWUS036ACS dongle acting as a 5.8 GHz illuminator. This system, using a pair of high-gain horn antennas (covering roughly 4.9–7.0 GHz), was mounted on a linear rail (from Israeli Aerospace Industries, IAI) to scan over a distance. A couple of Mini-Circuits RF splitters (model ZADC-10-63-S+ and ZADC-10-64) were employed, likely to distribute signals between components, and data was streamed via ZeroMQ sockets. In practice, this rig functioned as a mobile SAR platform, producing radar images of a local area by using a Wi-Fi signal as the radar source. It demonstrated that even a modest computer like the Pi 4 can handle real-time data acquisition, deferring heavy processing (image formation) to offline computation.
Another example dove into pure passive radar- using two cheap USB TV tuner dongles (RTL-SDRs) locked to a common clock and sampling at 2.048 MS/s (million samples per second). In this setup, one Yagi antenna was trained on a known digital TV transmitter (a DVB-T station in Sendai, Japan), while a second antenna (likely another directional Yagi) monitored the patch of sky or ground where a target (such as an aircraft or vehicle) might be located. This passive bistatic radar setup did exactly what theory described – it captured direct TV signals and their echoes from a target, then cross-correlated them. Impressively, the data from this experiment was made public on a community platform (iqengine.org), inviting anyone to explore the raw recordings. The ability to detect a target via broadcast television signals – using $30 dongles and open-source GNU Radio code – highlights how far the democratization of sensor tech has come. What once required a defense contractor’s lab can now be done by a determined hobbyist with patience and programming skills.
A third project took the concept to the skies- a bistatic radar using the European Space Agency’s Sentinel-1 satellite as the illuminator. Sentinel-1 satellites continuously broadcast radar pulses down at Earth for imaging purposes; Friedt’s team repurposed those pulses. They set up a B210 SDR and Pi 4 on the ground to listen for Sentinel-1’s signal bouncing off a target area. They pointed antennas at the right place and time by knowing the satellite’s trajectory (via tools like Heavens-Above for tracking orbital passes). The recorded data was later processed in MATLAB, performing range compression and azimuth compression (techniques to focus the radar image), effectively treating the satellite as the transmitter and its ground station as a passive receiver. They even had to account for clock drift over the one-minute pass. The result was a form of space-surface bistatic SAR, showcasing that even orbiting radars not intended for collaboration can be harnessed for imaging or tracking purposes. The SAR is a remarkable example of opportunistic sensing, using a trillion-dollar asset (an Earth observation satellite) in tandem with a few-thousand-dollar ground kit to perform unique measurements.
Through these projects, Friedt illustrated a unifying theme- modern computing and SDRs allow radar experimentation with unprecedented flexibility and minimal cost. The same fundamental method – capture signals on two coherent channels and find correlations – underpins everything from detecting a drone by its TV signal reflections to imaging a landscape with Wi-Fi or satellite illumination. Each scenario only swaps the source of the signal and the geometry of movement. All processing was done with open tools (no proprietary black boxes), reinforcing the open-source ethic. Friedt’s work thus provided neat demos and a blueprint for others. Indeed, he published supporting materials on GitHub for anyone interested in the topic. The barrier to entry for advanced radar research has never been lower.
Why It Matters- Stealthy Detection and Electronic Warfare Implications (So What, Why Now)
The rapid advancement and accessibility of passive radar techniques come at a pivotal time. Modern battlefields – and conflict zones like Ukraine – are saturated with drones, cruise missiles, and stealth aircraft, all posing detection challenges to traditional radar. At the same time, electronic warfare is intense- any radar that emits can be located and often targeted by anti-radiation missiles or jammed. Passive radar elegantly addresses these problems- by emitting nothing, it becomes practically invisible to enemy sensors and immune to anti-radar weapons, while still performing the core function of detection. An example of the “have your cake and eat it too” quality is why militaries and innovators are gravitating towards passive systems now.
Why now? Several converging trends make passive radar especially relevant in the mid-2020s. Firstly, computing power and algorithms (many of which are drawn from the open-source community) have caught up to the demands of cross-correlation and real-time big data streaming. What was computationally prohibitive a decade ago can now be run on a single-board computer or a modest PC, thanks to Moore’s Law and clever software optimization. Secondly, the electromagnetic environment has never been richer in signals – digital TV, 4G/5G cellular, Wi-Fi hotspots, navigation satellites – providing a buffet of prospective radar illuminators. The term “electromagnetic smog” aptly captures the cluttered state of the spectrum, especially over cities and war zones; passive radar turns this clutter into an advantage, transforming what was once considered RF pollution into a treasure trove of surveillance opportunities.
Thirdly and most pressingly, adversaries are deploying new tactics to evade active sensors. Drones have become central to warfare, used for reconnaissance and as loitering munitions, so both sides (attackers and defenders) are highly invested in drone countermeasures. Standard anti-drone radars exist, but many drones attempt to fly at low altitudes or minimize emissions to evade detection. In late 2024 and 2025, a novel threat emerged on the Ukrainian battlefield: first-person-view (FPV) attack drones controlled via fiber-optic cables instead of radio (Defense Mirror, 2025). These drones, sometimes trailing a long spool of fiber behind them, nullify the usual RF detectors and jamming techniques – they do not broadcast anything and thus are effectively radio-silent. They also often carry onboard AI, reducing the need for constant communication. Traditional radar has difficulty spotting such small, low-flying objects, especially in cluttered terrain, and their lack of radio signals means approaches that sniff for control links are ineffective. For a time, these fiber-linked drones were deemed “undetectable” and “invulnerable” to electronic warfare, enabling surprise attacks.
Now, passive radar shows its worth dramatically. In July 2025, Russia’s state corporation Rostec announced a new three-coordinate passive coherent locator (3D PCR) designed to detect exactly those stealthy drones “invulnerable” to conventional methods (Rostec, 2025). Rostec’s system can detect the reflections from a small drone, even if the drone emits no signals of its own, by utilizing broadcast television and radio signals as illuminators. Because the passive radar itself stays quiet, the fiber-optic drone (and its operators) have no warning they are being tracked. Rostec’s radar can determine the target’s range, azimuth, and altitude – meaning a complete 3D fix – at distances of tens of kilometers for larger objects, such as light aircraft (Rostec, 2025). The development was explicitly framed as a counter to drones that were previously “impossible to jam and difficult to detect” (Lenta.ru, 2025). In effect, passive radar has negated the newest advantage in drone warfare. The timing is no accident – the urgency of the Ukraine conflict, where both Russia and Ukraine have been fielding innovative drones, has accelerated the need for such technology. Fiber-optic drones rose to prominence in 2024; by mid-2025, a counter had arrived. This cat-and-mouse dynamic illustrates why passive radar is important now – it provides a timely response to current threats.
Beyond drones, passive radar has significant strategic implications for detecting stealth aircraft. Stealth technology on jets and missiles is often optimized to dodge or absorb the frequencies emitted by common radars (like X-band or C-band frequencies from air defense radars). However, stealth designs have a harder time vanishing against a multitude of disparate frequencies coming from every direction – for instance, FM radio or digital TV signals bouncing off them from various angles. Years ago, European firms like Cassidian experimented with passive radar networks that use civilian broadcast signals to detect even stealth fighters (Aviation Union News, 2012). They found that integrating new digital receivers and signal processing could significantly extend the detection range and precision, enough to spot low-observable targets and even track objects in radar “shadows” (such as behind terrain). Now in 2025, those concepts are maturing into real systems showing a trend where stealth is countered by exploiting the enemy’s civilian infrastructure against them – a city’s TV towers might betray the presence of a “hidden” aircraft without that city ever realizing it was part of a detection network. It is a powerful concept- every transmitter out there becomes a potential part of the radar, and the stealthy object cannot silence them all.
Electronic warfare (EW) and countermeasures also enter a new phase with the advent of passive sensors. Since passive radars do not radiate, traditional EW has nothing to jam or locate. An adversary might attempt broadband jamming of all possible illuminators (e.g., blanketing the area with noise to drown out TV and radio sources), but that is extremely difficult and self-defeating – it would knock out communications and likely reveal the jammer’s position. They might try dropping decoys or reflectors to confuse passive radar, but distinguishing real targets via Doppler or trajectory might still be feasible for the passive system. In essence, passive radar tilts the EW game toward the sensor’s side. Passive radar is deceptive by nature – the enemy cannot easily determine if they are under surveillance or not, which also lends itself to a psychological impact. An example of information warfare is when soldiers operating stealth drones or aircraft must assume that unseen eyes could track them at any moment.
From an intelligence and narrative perspective, the promotion of passive radar capabilities also serves strategic messaging. When Rostec announced its new radar, it highlighted that previously “invulnerable” drones (often portrayed as a wonder weapon by their users) are now countered, shaping the narrative by undermining enemy confidence in those drones and bolstering domestic confidence that Russian technology can neutralize new threats. The language in Russian media referred to the fiber-guided drones as “unjamable,” but then immediately asserted that they can now be effectively detected (Lenta.ru, 2025; Defense Mirror, 2025). The term “invisible” gets flipped – it becomes clear that invisibility is temporary. This kind of narrative, amplified through press releases and news articles, is a classic example of cognitive influence in military technology- persuading both friend and foe that a balance has shifted. It may deter the enemy from over-relying on a capability and reassure one’s forces and public that the situation is under control despite the adversary’s innovations. We observe a form of narrative laundering, where a technical development (the passive radar breakthrough) is quickly disseminated through official channels (Rostec’s release), echoed by the media (Lenta, defense blogs), and eventually shapes the common understanding of the conflict’s technological edge. No disinformation is needed – the facts themselves serve a purpose, though surely presented in the best possible light. For instance, the Rostec system is touted as effective in urban clutter and at all times of day and weather (Rostec, 2025), implying it has no meaningful weaknesses. Such optimistic portrayals are typical of press releases; the reality of performance will only be seen in operation. Nonetheless, even the existence of this radar could influence enemy behavior, causing them to adjust tactics or waste effort trying to locate or confuse a sensor that is essentially ghost-like.
Russian Adoption- A Case Study in Passive Radar for Drone Defense
The Russian developments in passive radar, as briefly touched on, merit a closer look as they exemplify the field deployment and militarization of these technologies. The “3D PCR” (passive coherent radar) unveiled by Rostec’s Rosel electronics holding is essentially a field-ready embodiment of the concepts demonstrated by Friedt, with enhancements and scaling suitable for military use. The 3D PCR phased array antennas and multiple passive receiver elements, which cover a three-dimensional volume of airspace (Defense Mirror, 2025), can measure range via timing and determine direction precisely, much like a traditional active 3D radar uses its antenna steering by analyzing the phase differences of incoming signals across an array. The passive sensor network feeds its data into algorithms that calculate the target’s coordinates. Rostec claims the system can detect even small low-flying objects and track multiple threats. Crucially, they stress its performance in “complex urban environments” and against “low-RCS, low-altitude” targets (Rostec, 2025), implying robust filtering of multipath reflections – an area where Russia has considerable experience given its long history with passive “Kolchuga” type systems – and perhaps the use of several distributed receivers to triangulate positions.
One fascinating aspect is the Russian narrative’s focus on fiber-optic FPV drones. These drones (often used as one-way attack drones with a warhead) became prominent when hobbyist modifications in Ukraine allowed drones to be flown via a spooled fiber optic line to avoid jamming. The Defense Mirror report (2025) even included a photo of a captured Russian FPV drone with a 10-km fiber coil, noting that Russia has used them in certain regions. So, Russia is both employing such drones and now deploying a radar to counter them – a full circle of measure-countermeasure. Fiber drones essentially eliminate radio frequency emissions, meaning that an active radar or radio scanner was almost the only way to catch them, and even that was challenging. The Russians are effectively turning the environment against these drones – every building’s TV antenna or commercial radio tower becomes part of a mesh that senses the drone’s presence by using passive radar. The reflections from the drone’s body or its fiber tether (which might itself reflect radio waves due to its materials) give it away. Defense Mirror mentions that operators of fiber drones noticed the fiber glinting in sunlight made them move frequently; now, even if they hide from sight, the radar reflections could reveal them, likely forcing changes- perhaps drones will try using less reflective fiber coatings or stick to night operations. However, any such adaptation will be an uphill battle as long as ambient signals are plentiful.
We note that passive radar is also attractive due to its cost-effectiveness and ease of regulatory compliance. Rostec’s press release highlights that the 3D PCR “does not need any licensed frequencies” and can operate on relatively low power, unlike active radars, which often require significant energy for their transmitters (Rostec, 2025). In countries or scenarios where spectrum is tightly controlled or power supply is limited (e.g., a mobile unit in the field), these advantages are significant. Passive systems can be vehicle-mounted and relocated without requiring frequency approvals. They can also operate continuously without drawing attention to themselves. For unmanned systems, one could even imagine a passive radar deployed on a drone or balloon – it could snoop for other drones or aircraft without easily revealing its own presence.
Patterns and trends emerge here: Russia’s development mirrors Western experiments, but with a focused purpose (counter-drone) and likely with more resources to address the problem. Western hobbyists and academics have led the way in concept (there are numerous research papers and open projects on passive radar since the 2010s), and now militaries East and West are racing to operationalize it. It is telling that multiple nations are converging on the same idea simultaneously, indicating a technological inevitability. We see this pattern in other tech as well – for example, just as cheap drones became a global phenomenon, cheap anti-drone measures like passive radar are following suit globally.
Outlook- A New Radar Landscape (Impacts and Strategic Foresight)
The rise of passive and hybrid radar technology portends significant changes in both military and civilian domains. In warfare, the near-term impact is clear- stealth and electronic silence will no longer guarantee safety from detection. Combatants will need to assume that the enemy may be using passive sensing, which reduces the advantage of stealth aircraft in specific scenarios, as adversaries invest in passive sensor networks. It could also force drone operators to adopt counter-countermeasures – perhaps drones will deploy decoy reflectors or engage in clever maneuvers to confuse passive radars (for instance, staying very low to blend with ground clutter or flying alongside other objects). We can also expect integrated air defense systems to include passive radar nodes networked with active radars. The passive nodes can cue active fire-control radars more safely, or serve as the early warning that gets the active systems pointed in the right direction. In effect, air defense could become a two-tiered system where silent sentries detect and track, and only at the last moment do active radars or missiles with seekers engage the target, minimizing the active emissions window.
Another impact is on electronic intelligence (ELINT) and suppression of enemy air defenses (SEAD) missions. Today, SEAD missions (such as NATO’s Wild Weasels or Russia’s anti-radar strikes) rely on detecting enemy radar emissions and destroying those emitters. In a world where enemy sensors do not emit, SEAD must shift tactics. Forces may need to locate passive sensors through other means – perhaps human intelligence, or detecting their communication links (passive radars still need to send their data somewhere). Alternatively, new munitions might blanket areas with fragmenting dipoles or tailored jamming to try to blind passive systems, but these are speculative. What is certain is that fighters and Wild Weasel aircraft will have a harder time if silent observers are watching the sky, driving the development of anti-radiation drones that flush out passive sensors by deliberately acting as bait, or broader spectrum surveillance to catch any unintended emissions from passive systems (even if the radar is passive, its electronics might leak some RF noise or it might rely on timing signals like GPS that could be detected).
On the other hand, passive radar offers benefits to civilian security and scientific applications. Airports and cities concerned about drone intrusions could deploy passive radar grids that monitor the skies without adding more radio interference to an already crowded spectrum. Such systems might be relatively low-cost, as they can leverage existing broadcast infrastructure. We might also see hobbyist and citizen science groups using passive radar for purposes like meteor detection (bouncing radio waves off ionized meteor trails, which has been done using TV transmitters) or tracking satellites by their transponders’ leakage. In the scientific realm, passive radar techniques could help map environments in novel ways – for example, using ambient signals to image a disaster site through smoke (where optical methods fail) or to study wildlife movements without disturbing them with active sensor pings.
Looking further ahead, AI and machine learning are likely to become increasingly entwined with passive radar as the volume of data and subtlety of signals continue to grow. Machine learning algorithms could better distinguish actual moving targets from the myriad false alarms (such as birds, wind turbines, and moving trees) that plague radar detection, especially in passive setups. AI could also optimize which signals to use at what time – for instance, dynamically picking the best frequency band out of many available broadcasts to track a given target, or even coordinating a network of passive sensors to focus on specific areas. The Defense Mirror article notes that the fiber-optic drones themselves often carry AI for autonomy; it is an interesting symmetry that AI on the defense side (in passive radars) will battle AI on the offense (onboard drones). We may witness an algorithmic duel in the RF domain, each side trying to outsmart the other’s signal processing or detection logic.
A critical consideration is proliferation. As the know-how and hardware for passive radar are now widely available, non-state actors could also adopt them. A terrorist or insurgent group might use a passive radar to secretly monitor military air traffic if they operate near a city with many TV towers, for example. While that scenario is complex, it is not implausible given the open availability of tools. This democratization means militaries might have to practice emission control not just to avoid state adversaries, but also to evade guerrilla observers. Conversely, peacekeeping forces or UN observers could utilize passive radar to monitor conflict zones without violating spectrum agreements or announcing their presence – it could become a tool for covert verification of ceasefires or movements.
Strategic foresight suggests that in any future high-intensity conflict, especially one involving near-peer adversaries, passive detection systems will be ubiquitous. We can expect nations to invest heavily in passive radar networks that cover their borders and critical sites, often integrated with other sensors (electro-optical, infrared) to form multispectral surveillance that is resilient against stealth. The side that better fuses and filters this flood of data will have an edge. We also foresee an “electronic cat-and-mouse” continuing- as passive radars spread, the development of counter-stealth measures may pivot to reducing RF reflections. That could mean new radar-absorbent materials effective even against broad-spectrum or out-of-band frequencies, or active cancellation systems on aircraft that sense incoming signals and generate canceling waves (an area of ongoing research). Drones might incorporate tactics such as dragging decoy reflectors or releasing clouds of chaff-like material to create confusing reflections for passive radar.
In the information sphere, as each new sensor is unveiled, expect both sides in any conflict to announce their latest counters loudly. Just as Rostec declared fiber drones are now detectable, one can imagine a future announcement that “stealth cruise missiles can no longer hide” due to passive radar, or on the flip side, claims that “our new drone has a radar transparency feature making it invisible again.” These statements shape perceptions and force adversaries to react even if they are not 100% true. Thus, technical realities and psychological operations will continue to intertwine.
Conclusion
In summary, passive radar technology has moved from theory and hobbyist tinkering to the forefront of contemporary security needs. Jean-Michel Friedt’s 2025 hacker camp experiments demonstrated that with innovation and off-the-shelf hardware, radar systems can be built to exploit the environment’s signals for detection – all without making a sound themselves. At the same time, real conflicts are demanding exactly these capabilities- the advent of drones and stealth threats that evade traditional detection has accelerated the adoption of passive radars by state actors. Russia’s deployment of a passive coherent radar to counter silent fiber-optic drones exemplifies how an idea can leap from a conference demo to a battlefield asset in a short span of time. The strategic benefits are clear- covert operation, immunity to jamming and anti-radar strikes, and the ability to detect targets once thought elusive. We are witnessing a paradigm shift where radars no longer need to be loud, and where the ever-growing cloud of ambient signals becomes an ally rather than an annoyance.
The impact so far has included greater situational awareness in complex environments and a check on novel threats, such as radio-silent drones. The future impact will likely be even more transformative. As these systems proliferate, actors who rely on not being seen – whether that be a stealth bomber or a tiny quadcopter – will find it increasingly challenging to achieve surprise. Warfare could become more transparent in some respects; the fog of war thins when unseen observers are everywhere. However, the duel between detection and evasion will continue, just on a new playing field of passive sensing and clever countermeasures. Moreover, the open-source nature of many passive radar advances means innovation is not limited to superpowers. We can expect continued cross-pollination between the DIY community and the defense industry, resulting in radar advances at a pace faster than traditional military R&D alone would allow.
In conclusion, the marriage of SDR technology with radar techniques is reshaping the sensor landscape. Passive radar stands out as a timely solution to 21st-century threats, and its rise underscores a broader truth- sometimes the best way to see is to remain unseen. The ongoing refinement and deployment of these systems will require careful analysis and adaptation by militaries worldwide. Those who invest in passive sensor networks and the data science to exploit them will hold a distinct advantage in the subsequent conflicts. Those who lag may find their stealth assets exposed and their electronic tricks outwitted. The radar revolution is quiet – literally – but its effects are echoing loudly through both tech circles and conflict zones, and that silence speaks volumes about the future of surveillance and electronic warfare.
References (APA)-
Admin (RTL-SDR). (2025, August 29). WHY2025 Conference- Passive and Active RADAR using Software Defined Radio [Blog post]. RTL-SDR.com. Retrieved from https-//www.rtl-sdr.com/why2025-conference-passive-and-active-radar-using-software-defined-radio/
Defense Mirror Bureau. (2025, July 17). New Russian radar tracks drones having fibre optic cables, AI brain. Defense Mirror. Retrieved from https-//www.defensemirror.com/news/39880
Rostec. (2025, July 9). Rostec’s solution can detect stealthy fiber-optic drones [Press release]. Retrieved from https-//rostec.ru/en/media/news/rostec-s-solution-can-detect-stealthy-fiber-optic-drones/
Иринин, Д. (2025, July 9). «Ростех» разработал радар для поиска «неуязвимых» дронов [Rostec developed a radar to find “invulnerable” drones]. Lenta.ru. Retrieved from https-//lenta.ru/news/2025/07/09/rosteh-razrabotal-radar-dlya-poiska-neuyazvimyh-dronov/