The idea

Active radar gives away your position the moment it transmits. Small drones and stealth-shaped airframes are designed to defeat the radar cross-section assumptions of monostatic radar in the first place. Skycifer’s Passive Mesh Radar solves both problems by not transmitting at all.

A swarm of low-cost SDR sensor drones flies in a mesh and listens. Each node captures the ambient RF environment — friendly ground radar emissions, broadcast television, cellular, even satellite downlink — and the reflections that targets cast off those sources. Skycifer’s adaptive AI fuses those returns across the mesh to build a passive air picture.

Why it works

• No transmit license required. Pure receivers — no FCC / NTIA spectrum coordination headache, and nothing for the adversary to home in on.
• Distributed geometry. Multi-static fusion across N nodes gives a far better detection-and-track problem geometry than any single point sensor.
• Cheap per node. Each drone is attritable. Losing one degrades the mesh; it does not blind it.
• AI does the hard part. Closed-form bistatic detection is brittle in a real RF environment. Skycifer’s adaptive ML learns the ambient and the targets together.

What it sees

• Small drones (FPVs, group-1 / group-2 UAS)
• Low-RCS and shape-stealthy airframes that conventional radar struggles with
• Surface contacts where the mesh overflies littoral water
• Ground-emitter geolocation as a by-product (the mesh hears them anyway)

Status

Passive Mesh Radar is a forward research line at Skycifer. The same SDR + adaptive-AI stack that powers Spectrogram AI provides the per-node sensing primitive. Government partners interested in early evaluation of the mesh-fusion pipeline are encouraged to engage early.