Collect and process aviation related emitters such as ACARS, aircrat transponders, UAT and ADSB.

I want to know more about the aircraft around me such as what a "normal" level of activity might be or the types of aircraft. Since I am only interested in aircraft which operate locally, and I don't need geographic displays etc. (already well supported by websites such as ADSBexchange).

In addition, I want to know more about the aircraft than is reported via ADSB (i.e. aircraft model and registration). To learn more, I use ADSBexchange which offers an inexpensive REST API. For best results, I collect from ADSBexchange on each observation.

To learn about nearby aircraft, I have set up multiple collection stations to observe ADS-B and UAT broadcasts. The observed broadcasts are collected into a PostGreSQL instance for analysis and simple reports are generated.

UML Component Diagram here

ADSB Collection runs on a standard Raspberry Pi using a rtl-sdr running dump1090 or dump978.

Collection runs once per minute from cron(8). The collected output is written to json formatted file and uploaded to AWS S3 for later processing.

There can be multiple collection stations writing to AWS S3.

More on ADSB collection here and UAT collection here

Processing consists of moving collected ADSB observations from S3 to a machine for parsing and loading into postgres.

More on observation processing here

mellow-hyena produces simple reports about upload and observations.

More on reporting here

1. Mode-S.org
2. ADSB exploit
3. ICAO UAT Tech Manual