01 The problem
One big radar is a powerful sensor and an obvious weakness
For decades, air surveillance meant a large, expensive radar: the more you could see, the bigger and more central the sensor. That model is being overturned by cheap, small, low-flying drones. They reflect almost nothing, they move slowly, and they arrive in numbers, exactly the targets a single large radar handles worst. And a single large radar is easy to find, jam or destroy. When it goes down, everything relying on it goes blind at once.
The alternative is to stop thinking about one sensor and start thinking about many. Instead of one powerful eye, a web of modest ones (spread out, networked, each contributing a fragment) combined into a single shared picture. That shift, from centralised sensing to distributed sensing, is what changes the signal-processing problem, and it is where our research sits.
02 Why it matters
The cost balance of air defence has inverted
Recent conflicts have shown a stark asymmetry: the threat is now far cheaper than the interceptor sent to meet it, and it arrives in numbers. No budget wins that exchange for long. The strategic answer is not a bigger sensor but a cheaper, more resilient network of them, and the economics reward whoever can process many low-cost signals into decisions faster. For Europe, this is also a question of sovereignty: building this capability at home, on components it can source, under its own control.
Resilience
A distributed network has no single point of failure. Losing one node degrades the picture slightly. Losing one big radar loses everything. Survivability comes from the architecture itself, not from add-ons.
Affordability
Many low-cost sensors can cover ground that one exquisite system cannot afford to. Cost per unit of coverage is what decides whether a defence can be maintained at all.
Sovereignty
A decentralised defence is only worth having if it stays under national control: built in Europe, on components that can be sourced, without depending on an outside supplier.
03 Why it is hard
Many cheap eyes are only useful if they agree
A distributed radar network trades one hard problem for another. Each individual sensor is weaker and noisier, the targets are the hardest kind to see, and the whole point, a single coherent picture, only emerges if scattered, imperfect observations can be fused correctly, quickly, and often without a reliable link between the nodes.
Targets that barely reflect
Small, slow, low-flying drones return almost no signal and hide in ground clutter. Pulling them out of the noise is at the edge of what a single low-cost sensor can do.
Fusing disagreeing sensors
Different nodes see the same object differently, at different times, with different errors. Merging those views into one trustworthy track, without inventing ghosts or dropping real targets, is the core difficulty.
Contested, jammed spectrum
In a real engagement the electromagnetic environment is actively degraded. Processing has to keep working when signals are jammed, spoofed or crowded, not only in clean conditions.
Comms you cannot rely on
Nodes may be unable to talk to each other continuously. The network has to build a useful picture even when the links between sensors are intermittent or cut.
Decisions in real time
A track that arrives too late is worthless. All of this has to happen fast enough to act on, on hardware small and cheap enough to deploy in numbers.
On sourceable hardware
Doing this at the edge, on components that can be procured under sovereign control, rules out the easy path of throwing unlimited compute at the problem in a data centre.