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The Paradigm Shift in Electronic Warfare
Modern conflict is undergoing a quiet but profound transformation in the way militaries approach electronic warfare (EW). The old model—platform-centric, siloed systems—has given way to distributed, network-enabled architectures that leverage unmanned aerial vehicles (UAVs) and autonomous swarms. This evolution is not optional; it’s a direct response to adversaries fielding increasingly sophisticated capabilities. Agile, networked RF sensing and communications allow opponents to detect and counter conventional EW faster than ever. Defensive systems now integrate cognitive EW functions, adapting in real-time to jamming attempts. Even the widespread availability of commercial RF technologies has lowered the barriers to entry, enabling state and non-state actors to field surprisingly capable systems at low cost.
Recognizing this shifting threat landscape, the U.S. Department of Defense’s Electromagnetic Spectrum Superiority Strategy reframes the fight for dominance in the invisible battlespace. It merges traditional EW with spectrum management into unified Electromagnetic Spectrum Operations (EMSO), anchored by five strategic goals: delivering superior EMS capabilities, building agile and integrated EMS infrastructure, ensuring total force EMS readiness, forging robust international partnerships, and establishing strong governance across the spectrum enterprise.
The Power of Distributed EW Networks
Distributed EW systems, particularly when enabled by UAV swarms, unlock a level of adaptability and reach that was previously impossible. For situational awareness and targeting, they provide real-time geolocation of hostile emitters across vast areas, feeding into an automated threat classification process powered by machine learning. The result is a constantly evolving electronic order of battle, allowing commanders to anticipate enemy moves rather than merely react.
In the realm of electronic attack and protection, these networks bring adaptive jamming that changes in sync with evolving threats, coordinated deception using synchronized decoys, and spectrum masking techniques that conceal friendly force movements. Network resilience is another hallmark—mesh architectures ensure that even if some nodes are lost, the system degrades gracefully rather than collapsing entirely. Anti-jam communications preserve connectivity in contested conditions, ensuring that mission-critical data continues to flow.
Integration with Unmanned Systems and UAV swarms
The proliferation of unmanned systems has accelerated the adoption of distributed EW. Small UAVs, ground robots, and autonomous maritime vessels can carry compact EW payloads into contested areas with minimal risk to human operators. These unmanned platforms can operate in swarms, using artificial intelligence to autonomously adjust their tactics in response to evolving threats.
The UAVs are able to digitally and instantly provide the most desired and precious operational information about the battlefield. They are eyes in the skies, over a battlefield that is crammed with high-resolution optics, data links, radars, and laser-guidance systems.
Unmanned systems bring distinct operational benefits to the EW mission set. They can loiter persistently over contested areas, offering continuous spectrum monitoring without risking manned aircraft. The UAVs’ advantage is an ability to loiter, often at a high altitude over a target, watching it ceaselessly for hours, if not days, and sometimes even weeks. In remote and unreachable areas, UAVs are quite effective tools because they conduct ISR without any detection by the enemy.
Their expendable nature makes them ideal for high-risk penetration missions, while their ability to maneuver in three dimensions allows operators to position them for optimal electronic effects. Most importantly, swarm configurations can be reconfigured on the fly, shifting roles or coverage areas as the tactical situation changes.
The concept of deploying autonomous UAV swarms to blind, confuse, and overwhelm an adversary’s integrated air defense systems, as well as other critical sensor and communication nodes, has long been recognized as a powerful and versatile military tactic. These swarms, operating with coordinated precision, can saturate an enemy’s detection and response capabilities, creating chaos within their defensive network. By leveraging distributed, autonomous decision-making, such formations can adapt in real time to changing threats, ensuring mission success even in contested and electronically degraded environments.
Executing these operations in the early stages of a conflict offers significant strategic advantages. By disrupting and degrading enemy defenses from the outset, UAV swarms can clear safe corridors for both manned and unmanned follow-on aircraft, including less survivable, non-stealth platforms. This not only facilitates the delivery of precision kinetic strikes but also enables other critical missions, such as intelligence, surveillance, and reconnaissance (ISR). In essence, UAV swarms serve as both the spearhead and shield of modern aerial campaigns, shaping the battlespace for decisive action.
Distributed EW enables capabilities such as wide-area denial of GPS signals, swarm-based jamming of enemy datalinks, and coordinated decoy operations to mislead adversary air defense networks. For example, during an air campaign, a swarm of UAV-based jammers could saturate an enemy’s radar picture while manned strike aircraft exploit the confusion to penetrate defenses.
From a technical standpoint, UAV swarms have several built-in advantages. Operating closer to targets reduces the power required for effective jamming, while distributed apertures allow coherent, multi-node operations that enhance both detection and deception. Their low observability profiles improve survivability in hostile airspace, and modular payload bays make them easily adaptable for different mission sets—from SIGINT to communications relay to active jamming.
Cutting-Edge EW Payloads for UAVs
Advances in miniaturization have enabled UAVs, even relatively small ones, to carry payloads that once required full-sized aircraft. Signals intelligence (SIGINT) packages can now monitor broad swaths of the spectrum, collecting both electronic intelligence (ELINT) and communications intelligence (COMINT). Electronic attack modules deliver precision jamming and deception, while expendable decoys can create false radar signatures or simulate high-value targets to draw enemy fire. Horizon-extension payloads turn UAVs into airborne relays, knitting together dispersed forces into a unified sensing and effects network.
Systems like Leonardo’s BriteCloud, Lockheed Martin’s Air Large, Raytheon’s MALD, and the U.S. Army’s ALE Family of Systems demonstrate the breadth of options available to mission planners today.
Enabling Technologies for Swarm EW
Several enabling technologies underpin the success of UAV-based distributed EW.
There are a variety of potential payloads suitable for mini-UAVs. These include communications & electronic intelligence (SIGINT) payloads, communications and radar jammers, electro-optic, infra-red, and MAW sensors, MTI and SAR radars, BDA sensors, comms relays, EW self-protection suites, chemical, biological, & nuclear detectors, target designators, and “horizon extenders”. Breakthroughs in miniaturization and low-SWaP (Size, Weight, and Power) design mean that advanced EW payloads can now be mounted on small UAVs, loitering munitions, or even handheld devices.
Finally, secure, resilient communications protocols ensure distributed EW nodes can coordinate effectively, share threat libraries, and operate autonomously if cut off from central command.
Equally critical are resilient network architectures. Flying ad hoc networks (FANETs) maintain connectivity even when nodes are moving at high speed or operating in contested airspace. Open standards such as SOSA and CMOSS ensure interoperability across platforms and vendors, while edge processing allows decision-making to happen directly on the UAV, reducing latency and dependence on vulnerable long-haul links.
On the hardware front, gallium nitride (GaN)-based amplifiers deliver high-power effects in compact packages, software-defined radios provide waveform agility, and phased-array antennas enable rapid, directional energy focusing.
Intelligent Agents
Autonomous systems powered by intelligent agents allow adaptive mission execution with minimal human oversight, while embedded machine learning models process the electromagnetic environment in real time. Collaborative algorithms let swarms self-organize, optimizing coverage and effect without requiring centralized control.
The integration of artificial intelligence and machine learning (AI/ML) enables near-real-time signal analysis, threat identification, and adaptive jamming strategies without relying on constant human input.
Artificial intelligence and machine learning bring the power of adaptive decision-making to the edge. AI-driven algorithms can analyze the electromagnetic environment on the fly, select optimal jamming strategies, and execute them autonomously while remaining aligned with the commander’s intent.
When the control of advanced payloads is combined with autonomous UAV navigation through Intelligent Agents, supported by a robust communications architecture, swarms gain the ability to adapt dynamically to changing environments. These agents can share information seamlessly, allowing each UAV to operate in coordination with others while pursuing both collective and individual mission objectives. This distributed decision-making model transforms a swarm into a cohesive, self-organizing force where the strengths of individual units amplify the capabilities of the group as a whole
Flying Ad Hoc Networks (FANETs)
Flying Ad Hoc Networks (FANETs) extend the concept of mobile ad hoc networks (MANETs) into the aerial domain, enabling UAVs to establish self-organizing, infrastructure-free communications. These networks link multiple UAVs—either directly or via intermediate relays—to a base station, which may be ground-based, airborne, or even space-based. FANETs differ from MANETs and vehicular ad hoc networks (VANETs) in key areas such as node mobility, rapid topology changes, and the impact of aerial radio propagation, all of which impose unique design challenges in latency, reliability, scalability, and energy efficiency.
In a FANET, only a subset of UAVs needs a direct link to a base station or satellite, reducing overall bandwidth demand and enabling large-scale, distributed operations. This architecture supports mission-critical functions such as cooperative sensing, distributed electronic warfare, and resilient communications in contested environments. By enabling UAVs to dynamically reconfigure their network paths, FANETs ensure connectivity even when individual nodes are lost or jammed, greatly enhancing swarm survivability and operational reach.
Embedded AI
The full potential of Intelligent Agents and FANETs depends on the availability of efficient, onboard artificial intelligence. Because UAVs are constrained by size, weight, power, and thermal limits, they cannot rely on large ground-based servers or GPU clusters for real-time decision-making. Instead, embedded AI solutions, leveraging specialized processors, field-programmable gate arrays (FPGAs), and heterogeneous computing architectures, enable sophisticated autonomy within these constraints.
Advances in high-performance analog-to-digital and digital-to-analog converters, combined with the integration of FPGA fabric and general-purpose processing on a single chip, have made it possible to run complex machine learning models onboard. This capability reduces latency, improves reliability in denied environments, and increases survivability by eliminating dependency on vulnerable external communications links. In swarm EW operations, embedded AI ensures that UAVs can interpret signals, adapt tactics, and make mission decisions without waiting for remote commands.
Cutting-Edge EW Payloads for UAVs
Electronic Surveillance (ES) Payloads
Electronic Surveillance (ES) and Signals Intelligence (SIGINT) payloads play a pivotal role in building a comprehensive and accurate situational awareness picture. By intercepting and processing adversary emissions—whether radar signals, communications, or other electronic signatures—these systems can update the Electronic Order of Battle in near real time. The real strength of ES lies in its ability to integrate data from a wide array of platforms, merging electronic information with imagery and other intelligence sources for a richer operational picture. Since ES systems are passive, requiring only reception and processing of signals, they demand far less power than active systems. This makes them ideally suited to miniaturized UAV platforms, where payload capacity and energy availability are constrained.
Traditionally, the highest-precision ES sensors have been mounted on high-value assets, operating at standoff distances of 100 km or more for safety. However, smaller and more affordable sensors, though less capable individually, can be deployed on expendable UAVs that operate much closer to the target—standing in rather than standing off. This proximity not only improves the accuracy of the data but also allows for the deployment of many more units at lower cost. Studies have shown that networks of these lower-cost sensors can deliver error rates up to 50% lower than those of a single, more expensive standoff system. The result is a distributed, resilient surveillance network that is harder to disable and capable of rapid re-tasking in dynamic battlespaces.
Electronic Attack (EA) Payloads
Electronic Attack (EA) payloads, such as jammers, traditionally require significant power when operating from standoff ranges, in part to ensure the safety of the platform carrying them. However, miniaturized UAVs, by virtue of their expendability and stealthier profiles, enable a “stand-in” approach, allowing them to operate much closer to the target. This proximity reduces the power needed to achieve the desired jamming effect while improving precision and reducing the risk of electromagnetic fratricide. Smaller coverage footprints from close-range jamming mean friendly systems are less likely to be inadvertently affected.
Operational analysis demonstrates the efficiency of this approach: a 100-watt jammer positioned just 10 km from an enemy radar can achieve the same jamming-to-signal ratio (JSR) as a 10-kilowatt jammer located 100 km away. Considering that many modern weapon systems have engagement ranges exceeding 100 km, and that mini-UAVs are inherently harder to detect due to their low radar cross section and infrared signature, this makes stand-in EA a highly viable option. Even if detected and engaged, the small size and signature of these drones mean that incoming weapons may fail to fuse correctly, further increasing their survivability. This combination of reduced cost, lower power requirements, and higher survivability positions stand-in UAV jammers as an attractive alternative to traditional EW platforms.
Horizon Extenders
Beyond active surveillance or attack roles, UAVs can serve as highly effective “horizon extenders,” essentially acting as airborne relay nodes or “flying antennas.” In this role, the UAV may carry only basic signal reception and transmission hardware, supplemented by modest onboard processing, signal time-stamping, and amplification. The bulk of the heavy data processing can remain on the ground or aboard a more capable host platform, while the UAV simply relays collected signals back to these facilities.
This approach significantly extends the line-of-sight (LOS) range of ground-based or shipborne systems. Even at relatively low altitudes—around 500 meters—LOS ranges of up to 100 km are achievable. This capability enables commanders to monitor, communicate, and coordinate well beyond the natural horizon without having to risk larger, more expensive airborne assets. Control of the UAV can be managed from the launch point, or by forward-deployed operators, such as those aboard ships or within tactical ground units. This flexibility, coupled with the affordability of small UAV platforms, makes horizon extension a valuable force multiplier in both surveillance and communications roles.
Modern miniaturization enables sophisticated EW capabilities on small platforms:
| Payload Type | Capabilities | Example Systems |
|---|---|---|
| SIGINT | Spectrum monitoring, ELINT/COMINT | Leonardo BriteCloud |
| Electronic Attack | Spot/barrage jamming, deception | Lockheed Martin Air Large |
| Decoys | False signatures, target simulation | Raytheon MALD |
| Horizon Extension | Communications relay, sensor netting |
Intelligent Agents
When the control of advanced payloads is combined with autonomous UAV navigation through Intelligent Agents, supported by a robust communications architecture, swarms gain the ability to adapt dynamically to changing environments. These agents can share information seamlessly, allowing each UAV to operate in coordination with others while pursuing both collective and individual mission objectives. This distributed decision-making model transforms a swarm into a cohesive, self-organizing force where the strengths of individual units amplify the capabilities of the group as a whole
Flying Ad Hoc Networks (FANETs)
Flying Ad Hoc Networks (FANETs) extend the concept of mobile ad hoc networks (MANETs) into the aerial domain, enabling UAVs to establish self-organizing, infrastructure-free communications. These networks link multiple UAVs—either directly or via intermediate relays—to a base station, which may be ground-based, airborne, or even space-based. FANETs differ from MANETs and vehicular ad hoc networks (VANETs) in key areas such as node mobility, rapid topology changes, and the impact of aerial radio propagation, all of which impose unique design challenges in latency, reliability, scalability, and energy efficiency.
In a FANET, only a subset of UAVs needs a direct link to a base station or satellite, reducing overall bandwidth demand and enabling large-scale, distributed operations. This architecture supports mission-critical functions such as cooperative sensing, distributed electronic warfare, and resilient communications in contested environments. By enabling UAVs to dynamically reconfigure their network paths, FANETs ensure connectivity even when individual nodes are lost or jammed, greatly enhancing swarm survivability and operational reach.
Embedded AI
The full potential of Intelligent Agents and FANETs depends on the availability of efficient, onboard artificial intelligence. Because UAVs are constrained by size, weight, power, and thermal limits, they cannot rely on large ground-based servers or GPU clusters for real-time decision-making. Instead, embedded AI solutions, leveraging specialized processors, field-programmable gate arrays (FPGAs), and heterogeneous computing architectures, enable sophisticated autonomy within these constraints.
Advances in high-performance analog-to-digital and digital-to-analog converters, combined with the integration of FPGA fabric and general-purpose processing on a single chip, have made it possible to run complex machine learning models onboard. This capability reduces latency, improves reliability in denied environments, and increases survivability by eliminating dependency on vulnerable external communications links. In swarm EW operations, embedded AI ensures that UAVs can interpret signals, adapt tactics, and make mission decisions without waiting for remote commands.
Operational Concepts in Action
Recent field trials and demonstrations offer a glimpse into what’s possible. Leonardo’s BriteCloud Swarm has shown how autonomous UAVs, each equipped with expendable decoys, can overwhelm simulated air defense systems without firing a shot. The U.S. Army’s Air Launched Effects program has demonstrated networked UAVs carrying modular payloads for intelligence, surveillance, reconnaissance, and electronic attack, integrated seamlessly with larger Gray Eagle platforms. DARPA’s CODE program has proven collaborative autonomy in contested environments, keeping communications resilient even under heavy jamming.
U.S. Army’s Air Launched Effects (ALE)
The U.S. Army’s Air Launched Effects program integrates a networked family of UAVs for both intelligence, surveillance, and reconnaissance (ISR) and electronic attack missions. These small, modular drones can be launched from manned or unmanned platforms—such as the MQ-1C Gray Eagle—and fitted with tailored payloads for jamming, spoofing, or sensor gathering. This modularity allows commanders to reconfigure forces on the fly, optimizing performance for evolving mission needs. The ALE network also enables real-time data sharing between air and ground units, significantly accelerating the sensor-to-shooter timeline.
Leonardo’s BriteCloud Swarm
Leonardo’s BriteCloud Swarm concept leverages autonomous UAVs equipped with expendable active decoys to saturate and overwhelm enemy air defense systems. In trials, these decoys mimicked the radar signature of full-sized aircraft, forcing opposing radars and missile systems to waste resources on phantom targets. By deploying in coordinated patterns, the swarm effectively demonstrated a non-kinetic suppression of enemy air defenses (SEAD), achieving the same operational outcome without the risks and costs associated with traditional strike missions.
DARPA’s CODE Program
DARPA’s Collaborative Operations in Denied Environment (CODE) program focuses on enabling UAV swarms to operate autonomously in heavily contested or GPS-denied battlespaces. These systems use advanced algorithms to make collective decisions, adapt behaviors in response to threats, and maintain mission effectiveness even under intense jamming. Demonstrations have shown resilient communications between swarm members, enabling coordinated EW effects without reliance on constant human control. By distributing tasks among multiple platforms, CODE swarms can persist in operations where individual UAVs would otherwise be neutralized quickly.
U.S. Navy’s Silent Swarm 2025 initiative,
The U.S. Navy’s Silent Swarm 2025 initiative, led by the Naval Surface Warfare Center Crane Division (NSWC Crane), is calling on industry to demonstrate small, disposable uncrewed vehicles equipped with advanced electronic warfare (EW) payloads capable of disrupting or destroying adversary communications, radar, and surveillance systems. The program envisions reconfigurable, networked platforms—air, ground, or maritime—that can target enemy RF communications; S-band, X-band, and navigation radars; as well as intelligence, surveillance, and reconnaissance (ISR) assets. These swarming assets will execute distributed electromagnetic attack, deception, and concealment, while delivering digital payloads, sustaining resilient communications, and supporting EW missions with geolocation precision.
Operating in the TRL 2–5 range, Silent Swarm emphasizes enabling technologies such as adaptive mesh networking, low-probability-of-intercept/low-probability-of-detection communications, multi-channel bandwidth agility, millimeter-wave links, free-space optics, and infrared sensors. Payloads will integrate narrowband and wideband jammers, advanced sensing, and geolocation tools, while swarming behaviors will be coordinated through AI/ML algorithms and alternative PNT solutions to ensure resilience in GPS-denied environments. By mimicking signals of interest, overwhelming adversary sensors, and manipulating RF signatures to congest and confuse the spectrum, these distributed EW platforms aim to degrade enemy situational awareness and decision-making, ultimately creating the tactical freedom for friendly forces to maneuver unopposed.
Pacific Defense’s Silent Swarm 2025: A Live Demonstration of the Future
The Naval Surface Warfare Center (NSWC) Crane Division is working with Pacific Defense on one of the most ambitious distributed EW programs to date—Silent Swarm 2025. This initiative envisions a highly modular and resilient EW architecture built around autonomous, cooperative platforms. Small UAVs equipped with digital RF memory (DRFM) jammers, spoofers, and signals intelligence payloads will operate in concert with ground-based EW stations and unmanned surface vessels.
Designed to meet CMOSS (C5ISR/EW Modular Open Suite of Standards) requirements, the system can accept rapid technology upgrades—ensuring it stays ahead of evolving threats. Its mission set includes corrupting enemy radar, GPS, and communications; denying situational awareness through clutter and false returns; and enabling friendly maneuver by blinding adversary sensors. The result is a self-healing, anti-jam network that remains operational even if individual nodes are destroyed.
As one Pacific Defense engineer described it, “You don’t have to win the spectrum everywhere—you just need to win it where and when it matters most. That’s what distributed EW gives you.”
The Future of Network-Centric EW
Emerging trends are set to push these capabilities even further. Cognitive EW systems will not just adapt—they will learn from every engagement, becoming more effective over time. The convergence of EW and cyber operations will allow forces to deliver synchronized multi-domain effects, while space-based EW layers will extend spectrum dominance to a truly global scale. Quantum sensing, still in its early stages, promises unprecedented sensitivity in detecting even the faintest adversary emissions.
As Pentagon strategist John Thompson aptly puts it: “He who emits first, dies. The future belongs to those who can see without being seen, and strike without warning in the electromagnetic spectrum.”
Conclusion: Winning the Invisible Battle
The move toward network-centric EW marks a fundamental shift in how militaries will fight—and win—the invisible battles of the future. UAV swarms, empowered by AI, advanced hardware, and distributed architectures, offer asymmetric advantages against peer adversaries, scalable effects across tactical and strategic levels, and the adaptability to counter emerging threats in real time.
With programs like Silent Swarm and ALE moving from concept to reality, the era of distributed, intelligent EW has already begun. The only question now is how quickly these systems can be fielded at scale—and which military will master them first.
References and Resources also include:
https://www.militaryaerospace.com/rf-analog/article/14198263/electronic-warfare-unmanned
