Drone Detection in Restricted Airspace

I had the opportunity to work on something I didn’t expect to find myself doing — real-time drone detection in restricted airspace, alongside public safety and defense environments.

The Problem

Large public events generate a lot of enthusiasm, and with that comes people flying consumer drones in places they absolutely shouldn’t be. In restricted airspace scenarios, especially around sensitive locations, that becomes a real problem quickly.

Despite that, a lot of teams on the ground don’t have a reliable way to detect drones in real time, let alone locate their operators. The assumption is usually that radar solves this, and while it can, deploying radar in a temporary public environment isn’t always practical. Regulatory constraints and setup time make it difficult to use in situations that require something fast and flexible.

That gap is what creates space for alternative approaches.

The Approach

The approach I worked on centered around passive RF sensing. Instead of transmitting, the system listens for the radio signals that drones and their controllers already emit.

Because it’s passive, it avoids the need for spectrum authorization and can be deployed quickly in environments where active systems would be harder to justify.

On top of the sensor, I worked on software to process and filter incoming detections. Raw RF environments are noisy, especially at large events. The goal was to reduce that noise into something actionable by prioritizing detections based on signal characteristics and relevance to the area of interest.

The result was a simple interface that allowed operators to visualize detections on a map and focus on what actually mattered. When something showed up in a restricted area, it gave responders a starting point to investigate and act.

What Surprised Me

What stood out the most was how early-stage this problem still is in many real-world environments.

The need is obvious. Drones are already showing up near sensitive locations and crowded events. The technology to detect them exists and isn’t particularly exotic. But between procurement timelines, regulatory friction, and lack of standardized tooling, there’s still a gap between what’s possible and what’s actually deployed.

Remote ID

Part of the reason this works at all is Remote ID.

Remote ID is the FAA’s broadcast identification standard for drones, similar in concept to ADS-B for manned aircraft. Compliant drones broadcast information like position, velocity, and a reference point for the operator over short-range radio.

A passive RF sensor can pick this up without transmitting anything, which makes it a practical foundation for detection systems.

The limitation is that it only works for compliant drones. If someone disables it or uses hardware that doesn’t follow the standard, you need additional techniques to detect them, which is where broader RF analysis comes in.

Takeaway

This was a small window into a much larger problem space, but it highlighted something important: there’s a real operational gap, and it doesn’t require overly complex solutions to start addressing it.

Passive RF sensing paired with simple software can be deployed quickly, avoids regulatory overhead, and gives responders something concrete to work with.

I’m still early to this space, but it’s one I’m paying close attention to. As drones become more capable and more common, the systems used to manage them will need to catch up.