This article discusses how low-frequency, multistatic, and passive radars expose stealth, and how SkySim turns theory into hands-on training.
Stealth is often misunderstood as invisibility. In reality, it is the result of carefully designed compromises. Aircraft reduce their radar cross-section by shaping, by coating themselves with radar absorbent materials, and by hiding their inlets, exhausts, and weapons bays. These optimizations work best against the radar frequencies and geometries for which they were designed. Move outside that narrow window, and the illusion of invisibility begins to fade.
This has led to a growing body of research showing how radars can exploit stealth’s blind spots. One well-documented approach is the use of low-frequency radars, operating in VHF or UHF bands. Because the wavelengths are long, they interact differently with an aircraft’s structure, sometimes creating resonance scattering. Studies confirm that shapes optimized for higher-frequency radars are often more visible when illuminated by lower bands, even if this comes at the cost of poorer resolution and bulkier antennas (Fraunhofer/IEEE study).
Another important direction is the use of multistatic or bistatic radar networks. Instead of a single transmitter and receiver co-located, these systems spread their sensors across different positions. Stealth shaping may deflect energy away from one receiver, but not necessarily from all. Researchers at Fraunhofer demonstrated that combining digital audio broadcasting signals with multiple passive receivers allowed detection of low-flying stealth targets in scenarios where conventional radar struggled. Such passive radar approaches are particularly intriguing: they exploit “signals of opportunity” like television, radio, or cellular transmissions, turning an adversary’s environment against them (IEEE Aerospace & Electronic Systems Magazine).
Signal processing innovations complete the picture. New algorithms suppress clutter, integrate weak echoes over long time windows, and distinguish genuine returns from multipath or ghost targets. For small, low-RCS drones in particular, progress has been rapid. A 2025 study in Drones showed that passive radar using digital audio broadcasting could reliably track small UAVs once advanced clutter suppression algorithms were applied (MDPI study). These techniques are computationally intensive, but they illustrate that stealth is never the end of the story: with clever mathematics, even weak echoes become visible.
For SkyRadar’s SkySim, the implications are clear. Training against stealth must go beyond showing an empty scope. Instead, cadets should experience how detection probability changes across frequency bands, how networks of receivers can catch what a single radar cannot, and how passive illumination from television or cellular towers can become unexpected allies. They should also learn about the trade-offs: low frequencies bring clutter, passive sources have limited resolution, and multistatic systems require precise synchronization. Only by practicing with these constraints does theory become operational knowledge.
Ultimately, counter-stealth is no longer a theoretical pursuit. From Iran’s Alim passive radar, which reportedly detects low-flying targets at several hundred kilometers, to European research into passive and multistatic systems, the world’s radar community has shown that stealth can be challenged. For training academies and air defense institutions, this means preparing operators not just to admire stealth from afar, but to engage with its weaknesses in hands-on practice.
By embedding counter-stealth techniques into SkySim, SkyRadar ensures that tomorrow’s radar officers are stealth-aware, but more importantly, stealth-prepared.
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