Detection pipeline
From aircraft broadcast to published alert. Stages marked as rolling out are in deployment and are not claimed as live capability.
- 01
Aircraft ADS-B broadcasts
Aircraft continuously broadcast position quality indicators (NIC, NACp and SIL) derived from their onboard GNSS solution.
- 02
Sovereign UK sensor network
Company-owned ground nodes on UK territory receive those broadcasts and aggregate them into grid cells over short time windows.
- 03
Direct RF interference measurement
Rolling out across nodesRF-capable nodes measure the GNSS bands themselves: noise floor, AGC, C/N0 and jamming indicators.
- 04
Post-quantum signed telemetry
Rolling outEach telemetry batch is signed with ML-DSA (NIST PQC) so its origin can be verified long after collection.
- 05
Encrypted transport
Signed batches travel to the sovereign ingest endpoint over authenticated, encrypted channels.
- 06
Real-time anomaly detection
Cell-level degradation is scored continuously; sustained clusters are promoted to interference events.
- 07
Tamper-evident evidence chain
Rolling outPeriodic Merkle roots over ingested telemetry are anchored to a permissioned blockchain for later forensic use.
- 08
Live map, API and alerts
Results are published to the public map and, for subscribers, to real-time feeds, webhooks and alerting.
How ADS-B reveals GNSS interference
Aircraft transmit not just their position but how much they trust it. NIC (Navigation Integrity Category) and NACp (Navigation Accuracy Category, position) collapse when the receiver loses confidence in its GNSS solution. A single aircraft reporting low integrity is unremarkable; dozens of unrelated aircraft doing so inside the same volume of airspace, at the same time, is a signature of interference on the ground or in the air. PNTMAP aggregates those reports per grid cell and per time window so the pattern, not the individual aircraft, is what raises an alert.
Direct RF sensing
ADS-B tells you that receivers are struggling. RF sensing tells you why. RF-capable nodes measure the GNSS bands directly: the noise floor in L1 and L5, receiver AGC behaviour, mean carrier-to-noise density across tracked satellites, satellite count, and hardware jamming indicators. Combining an airborne integrity signature with a ground-level RF measurement turns a statistical anomaly into a corroborated observation.
Jamming detection
Jamming raises the noise floor and starves receivers of usable signal. On the ADS-B side it looks like a sharp, spatially bounded rise in the proportion of low-NIC aircraft, often with a clear gradient towards the emitter. On the RF side it looks like elevated noise, depressed C/N0 and a rising jamming indicator with no corresponding change in satellite geometry. PNTMAP scores both, and where a degradation persists across successive windows it is promoted to a jamming event with a severity band.
Spoofing detection
Spoofing is harder: receivers stay confident while being wrong. The tells are inconsistency between independent observations: reported positions that disagree with the geometry of the signal actually received, implausible clock behaviour, and clusters of aircraft converging on identical false solutions. Robust discrimination requires multilateration cross-checks between several nodes observing the same aircraft, so spoofing confidence rises as the network densifies. With one node, PNTMAP reports what it can measure and says so.
Why provenance matters
Interference data is only useful if it can be trusted later, whether in a safety investigation, an insurance claim, a regulatory filing or a national security assessment. That means knowing which sensor produced a measurement, that the record has not been altered since, and that the operator is contractable and accountable. PNTMAP is being built so that every record carries a verifiable signature and sits under a periodically anchored Merkle root, rather than resting on the good faith of a distant third party.