AeroScope is not a roadmap deck, these capabilities are live on the platform right now. Each one maps to the same mission: see what is above you, know what it is, catch what is deceptive, and stay ahead of it in real time.
A live instrument HUD over your position, a rotating radar dome, an animated altitude histogram, and a drag-to-explore situational globe with connection arcs to the contacts that matter. Rendered entirely client-side with three.js.
adsb.fi, adsb.lol, airplanes.live and OpenSky plus a satellite-ADS-B merge, de-duplicated by ICAO 24-bit address, one airframe, not three dots. How fusion works →
60+ FEEDSEight weighted rule-based factors summed into an explainable 0–100 rank. Always shows its working; never an accusation. See the score →
8 FACTORSRiver, scikit-learn IsolationForest, a pykalman innovation test, OpenAP envelope checks, stumpy matrix profiles and PyOD, a flag fires only on ≥2-detector agreement. Detectors →
TORCH-FREEA DO-260B-style 7-check plus a Kalman normalised-innovation test and altitude/speed/heading residuals expose self-inconsistent messages. Integrity →
DO-260BRemote-ID parsing plus behavioural signatures, low-and-slow, tight loiters, surface candidate uncrewed aircraft. Drone detection →
REMOTE-IDClient-side dead-reckoning glides every aircraft at its true ground speed between fixes and corrects toward truth without snapping back. The pipeline →
DEAD-RECKONINGAutomatic orbit, racetrack, loiter and grid-search classification with per-airframe behavioural baselines for deviation scoring. Baselines →
BEHAVIOURALCircle and polygon zones with enter/exit events, emergency-squawk detection (7500/7600/7700) and observer-relative proximity thresholds. Geofence guide →
OBSERVER-RELATIVECSV, JSON and GeoJSON exports plus a documented REST/WebSocket API, reproducible analysis, not a black box. API docs →
CSV / JSON / GEOJSON| Capability | Implementation |
|---|---|
| Multi-source fusion | 60+ public feeds polled and merged on the ICAO 24-bit address, with a satellite layer for oceanic gaps. How fusion works. |
| Attention scoring | Eight weighted rule-based factors summed to 0 to 100, every contribution shown. The scoring method. |
| Integrity and spoof checks | DO-260B style NIC, NACp, NACv and SIL checks, a Kalman normalised-innovation test, and self-consistency residuals. Detection detail. |
| Consensus anomaly detection | River, scikit-learn IsolationForest, pykalman, OpenAP, stumpy and PyOD, flagging only on two-detector agreement. Baselines. |
| Drone heuristics | Remote ID parsing plus low-and-slow behavioural signatures. Drone detection. |
| Smooth live map | Client-side dead reckoning between fixes, positions refreshing about every seven seconds. |
| 3D airspace view | Radar dome, altitude histogram and situational globe rendered client-side with three.js. |
| Developer access | REST and WebSocket API, plus a public MCP endpoint for AI assistants. |
| Open data | CC-BY 4.0 anomaly benchmark, 38 documented columns. Research. |
Deliberately absent: deep learning, reinforcement learning, acoustic or radar sensing, and any claim of certification. See limitations.