The Changing Face of Electronic Warfare
Electronic warfare typically is defined as any type of manipulation of the electromagnetic (EM) spectrum. Thus, EW technologies range from radar and navigation to military communications. While the goal of EW remains to secure one’s own forces, near-peer developments pushed EW development into an ongoing competition. Fast-paced technology innovation creates an environment in which countermeasures and threats constantly work to stay ahead of each other. The result is a constant barrage of novel, advanced threats, which are challenging to detect and analyze.
Ten or more years ago, the EW environment looked and behaved very differently. The US was a dominant force with very impressive systems. The advent of commercial-off-the-shelf electronics made EW components cheaper, easing the path to an advantage in conflict zones. Software-defined systems also are being used more commonly, allowing threat creation as well as operation customization via aspects like software or firmware updates.
A multitude of diverse, complex threats results – often coming from near-peer adversaries that were not a concern in the past. These threats are more adaptable and reprogrammable. Waveforms change rapidly, making their characterization very difficult. Adaptable threat radars have taken the somewhat predictable battlefield of the past and replaced it with a fast-changing, hard-to-predict environment.
The New Threat Environment
Keeping up with these threats requires matching leaps in technology. In today’s dense signal environment, however, finding the signal of interest is highly challenging – especially when it can quickly change. Using traditional threat databases will not enable you to keep pace with today’s modern, fickle threat environment.
To mitigate threats, the first step is to detect, identify, locate radio-frequency (RF) emitters. To accomplish signal detection, you must be able to separate the relevant from the irrelevant data. It is not easy to provide actionable intelligence in a congested environment. With the rise of cognitive systems, some adversaries can find open spaces in the spectrum and shift to those frequencies.
In the race to provide actionable intelligence, artificial intelligence (AI) is boosting countermeasure capabilities. Specifically, machine learning is being employed to learn threat behavior and adapt accordingly, based on ongoing self-education about potential behavior. Yet a major problem still exists. As machine learning helps to enable countermeasures to sophisticated threats, it often fails to do so within operational timelines. The immense amount of processing involved demands much time in current systems. Yet they function in a potential war zone that cannot afford to wait for the right response.
Beyond AI, EW’s future may rest on an open architecture to combat threats. Traditional threat simulation solutions are custom products known for their long development times. In today’s EW world, however, a long timeline often means obsolescence by the time of delivery. And updates and upgrades at that point only add to the expense. With a larger partner network and a standards-based approach, countermeasures can better keep up with modern, rapidly changing threats – hopefully even surpassing them. While this path seems a likely trend for the future of EW, much is still hard to predict – except, of course, the increasing complexity of the EW environment.
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