Martin McCormick has introduced QuadRF, a handheld phased‑array radio that uses a Raspberry Pi 5 and an FPGA to detect Wi‑Fi signals through walls and track drones in flight.
Martin McCormick has introduced QuadRF, a handheld phased‑array radio that uses a Raspberry Pi 5 and an FPGA to detect Wi‑Fi signals through walls and track drones in flight. The device streams in‑phase and quadrature data over the Pi’s MIPI camera interface at more than 5 Gbps and operates in the 4.9‑6 GHz band.
QuadRF is a phased‑array antenna system built around a Raspberry Pi 5 and an FPGA board, allowing picosecond‑level timing for signal processing and beamforming. The open‑source project was inspired by SpaceX’s Dishy antenna and aims to let licensed operators chain multiple units for EME radio experiments and radio astronomy.
The device connects to a Wi‑Fi hotspot created by the Pi and presents a web page that runs a VNC session with GNU Radio, SDR software, and an augmented‑reality RF visualizer. In tests the visualizer displayed 5 GHz Wi‑Fi networks as colored blobs; a DJI Mini Pro 4 drone was detected and tracked as it flew past the studio. The UI includes controls for camera alignment and receiver gain, but gain adjustment can be awkward when the unit is carried.
A basic kit is offered through Crowd Supply for $499 and the campaign has exceeded its target, leading the team to replace the 3D‑printed enclosure with an injection‑molded case. The hardware can be expanded with a mobile pack that adds a battery and a handheld mount for real‑time C‑band analysis.
QuadRF streams I/Q data over the Pi’s MIPI lanes at rates above 5 Gbps, enabling low‑latency full‑duplex operation. Multiple units can be linked, each calculating its own phase shift, and the system can sustain hundreds of megasamples per second without sample loss.
The project remains open‑source and is intended for experimental radio work rather than commercial satellite applications. Final production details and availability have not been confirmed.
- Publisher
- Hacker News
- Reliability
- high
- Published
- 7/11/2026, 10:00:36 AM
- Retrieved
- 7/11/2026, 10:00:36 AM
- Relevance
- 80%
- Confidence
- 85%

