Luca Di Iorio Casellas

DJI DroneID location system

Reverse engineered the DJI DroneID protocol across OcuSync 2, 3 and 4 to build a drone location system driven entirely by an SDR.

Given nothing but raw spectrum, it recovers the aircraft and the operator's position straight out of the broadcast frames — no cooperation from the drone, and nothing to install on it.

DroneID spoofing device

A transmitter that emits modified DroneID data.

It exists to answer an uncomfortable question: how does a detection system behave when the identity broadcast it trusts is a lie? Ours included. You cannot harden what you have never attacked.

RemoteID detection module

Led both halves of this one: the team that designed the PCB and the team that wrote the firmware.

The module listens for the RemoteID broadcast that regulation now requires of every aircraft, and feeds it into the wider detection stack as just another sensor.

OcuSync 4 decryption server

Reverse engineered the communication protocol between the DJI Aeroscope and its Dongle, then rebuilt that exchange as an online OcuSync 4 decryption service.

The interesting part was never the cryptography on its own — it was working out which side of the conversation held what, from the outside.

OFDM RF detection device

Signal-level detection and reverse engineering of OFDM waveforms, turned into a standalone RF detection device.

Detection here happens below the protocol: you classify the shape of the transmission before anything has told you what it is.

What Shenzhen made obvious about air defense

I spent a week in Shenzhen at the 10th World UAV Congress & UASE Expo, and it became entirely clear that traditional air defense is no longer sustainable. We are witnessing a warfare shift where $500 FPV drones are successfully targeting multi-million-dollar assets. This is why the C-UAS industry is pivoting hard into advanced RF detection and dynamic interception.

On the detection side, the market is shifting to RF direction finding. Multi-sensor arrays measure the angle of arrival and time difference of arrival of incoming signals, and passively triangulate the exact 3D location of the threat.

Once detected, the response is evolving too. The most critical solutions on the expo floor were not static jammers but AI-driven interceptors — hit-to-kill drones with autonomous targeting, a low-cost decentralized defense layer capable of matching the volume and velocity of modern drone warfare.

The future of low-altitude security relies on that synergy: passively tracking the threat miles away, and deploying a scalable response to neutralize it.

The drone war is moving faster than traditional procurement cycles. Are our defense grids and critical infrastructures adapting fast enough?

Final project: Drone Detection with an RF Spectrum Analyzer

An RF spectrum-based drone detection system with a real-time monitoring interface — the first version of the problem I've been working on ever since.

Written in C++ with the Qt framework and QML for the interface, with multithreading and a REST API underneath.