Electronic Warfare:

ver the past decade, preeminent countries involved in major military conflicts mainly focused on asymmetrical warfare—surprise attacks by small groups armed with modern, high‑tech weaponry. During that same period, however, near‑peer adversaries began attaining impressive electronic warfare (EW) capabilities. As a result, a plethora of new, dynamic threats flooded the EW spectrum, pushing threat detection and analysis to keep pace.

Large military forces must now engage in ongoing development and evolution to stay ahead of their adversaries, leading to a need for a more flexible, scalable approach to threat detection, analysis, and response.

Even the smallest military can now build powerful weapons systems, given the availability and low cost of advanced electronics with high computing power. The proliferation of technology has also created a battlefield where weapons technology undergoes rapid, continuous change. Digital and programmable radio frequency equipment, such as software-defined radios, creates a more complex battlefield. In addition, radars can quickly change waveforms, making it challenging to locate, identify, and confuse hostile emitters.

These trends impact every aspect of EW, which uses the electromagnetic (EM) spectrum to sense, protect, communicate, and attack during warfare. Today, the ability to ensure spectrum-wide superiority during warfare is one of the biggest determinants of success or failure during a military operation.

• EW support is broadly defined as surveillance and reconnaissance using EM energy. The data gathered can produce signal intelligence (SIGINT) to help with targeting for an electronic or physical attack. It also can produce measurement and signature intelligence.
• Electronic attack uses EM energy, direct energy, or anti-radiation weapons to confuse, disable, or destroy an enemy’s electronic systems. Weapons used for electronic attack leverage lasers, electro-optical, infrared, and RF technologies.

The following are examples of modern warfare:

• Electronic deception techniques used to confuse an enemy’s intelligence, surveillance, and reconnaissance (ISR) systems; and
• Direct energy weapons with the potential to destroy people, materials, and equipment such as satellites, airborne optical sensors, and land-based forces.

This environment creates complex signal activity, leading to dynamic and evolving threats for EW systems. While many EW systems use technology advancements such as high-performance DSP and gallium nitride (GaN) amplifiers, the sheer number of possible scenarios from one threat creates difficult challenges.

Military technology is turning to machine learning to create cognitive EW weapons that can successfully operate in these environments. These weapons use software-defined capabilities to gain operational flexibility in congested (and contested) environments, quicker upgrades, and greater affordability.

Digital equipment can be programmed on the fly using software programs, allowing EW solutions like radars and software-defined radios to change waveforms and create unique signatures quickly. As more communications systems, radios, jammers, and IoT devices operate in the EM spectrum, spectrum awareness takes on increased importance. New EW systems look to understand the intent of each system using the spectrum, rather than relying upon assumptions about ideal scenarios regarding the environment, design/application challenge, or hardware like traditional systems. Such assumptions limit the potential for signal identification and other tasks, boosted by machine learning.

The procurement process also requires roughly three years for high-profile systems from order to delivery. Often, this timeline does not include further customization. Yet EW technology and threats progress at a nearly daily rate. In contrast, open architectures present a route to dynamically respond to the ever-changing threat environment.

An EW environment generation architecture that supports multiple hardware types and new technology insertion is key to keeping pace with rapidly evolving threats and reducing lead times for new systems and test capabilities. A common set of interfaces and non-proprietary file formats is also needed to develop simulator agnostic threat models that are not limited to use on only one vendor’s hardware. In the U.S., for example, the Next-Generation Electronic Warfare Environment Generator (NEWEG) program allows participation from multiple vendors simultaneously via a shared interface and the use of non-proprietary formats.

Scalability is key to the performance of modern EW systems. To ensure realism and confidence in EW system performance, the industry is adopting scalable architectures that enable flexibility in the way they test from early design through mission data validation. These architectures allow test assets to be reused across multiple platforms for decades with upgrades and reliable support, maximizing efficiency and reducing cost. As EW systems become increasingly adaptive, the ability to evaluate performance against complex, evolving scenarios in a scalable, repeatable manner is essential for maintaining assurance and mitigating risk before systems are deployed in the field.

Open architectures allow testing to keep pace with the latest threat environments while enabling more precise and comprehensive EW threat simulations. With the addition of advanced analysis capabilities, engineers can also automate signal and threat model verification. The goal of such testing is to ensure that EW systems remain current and highly effective while also saving valuable time and reducing the need for additional investments in the future. Open architectures enable EW systems to remain relevant in the face of new threats by characterizing, assessing, and responding to them as needed in real-time EW scenarios.

As threats evolve and change, your system must adapt. Countermeasures must also keep pace, striving to prevail over a constant stream of new threats. As the battlefield becomes increasingly crowded with devices that demand more of a limited spectrum, sorting through signals and identifying them is imperative. Future systems will move from being adaptive to using new AI and machine learning capabilities to decipher constant changes in spectrum use. Software-defined weapon technology allows for continuous upgrades without needing to invest in entirely new systems.

The new electromagnetic spectrum battlefield is increasingly challenging, and technology and weapons need to respond accordingly – even if it means breaking from the dependencies of past projects and adopting a flexible, scalable, open architecture approach.