UPDATE! I am writing up instructions and Node-RED flow code on my GitHub page:

Turns out that aircraft blat out more than just their positions.
They also send a lot of short messages that anyone can receive and to some extent decode and make some sense of.
This has been keeping me busy for the past month or so. Been really enjoying being distracted from other things, and my love of all things aircraft gets a good dose of love.
The fact that I also use Node-RED to decode the messages is also very helpful as I needed a project to dive deeper into it.

I started off with the freely available acrsdeco2 program and the real power of this program is that you can run remote instances of it and have it feed into a central server.
I sent a Raspberry Pi and two receivers to my mate in Phoenix and have his data added to what I can pick up. The net results is that we have pretty much the whole area now covered with just the two receivers. More would be good and we will look at adding a few more in due course, but for now, the two systems working as one does the job.

From there I added Node-RED. Doing a ton of reading got a lot of the abbreviations entered into the system and then I started filtering out the boring positions reports. I split off the airborne weather reports and engine reports.
I then added several displays that showed this filtered and partly decoded information.
The flow is by far and away the most complex I have done.

If you would like to watch the messages, you can, just hit up the resulting node-RED dashboard;

The top line is just helpful data for me to see how much data we are handling. Some quick links to other parts of the system and weather stations at each location are included.
Next is heavily filtered messages. At times I can see more than 1 message a second and they scroll past too fast to read, so I do some heavy filtering to slow the interesting stuff down.
Next is an aircraft call sign filter. If you want to follow a specific aircraft, this is the tool to use.
Next is the raw message. This way you can just what we are working with.
Below that is a way to stop/ start the raw lightly decoded messages.
Then you have the real interesting stuff. It is the result of the filter and should be interesting enough that we email it to a few of the guys and myself.
Below that, the reports and a table of last seen (heard) aircraft.

All in all, fascinating stuff.


  1. Hi baldgeek, my Name is Roy and I want to say hello !

    I live in Germany very close to Ramstein AB where I’m tailspotting and photographing for many many years now.
    I came across your website and your terrific aircraft / acars / inmarsat development, really impressive !
    I’m doing the ADSB stuff for several year now, in addition I started to dig in ACARS via Inmarsat aprox 2 years ago.
    With the support of Jeroen in Sweden I have for some time now a reliable system running.
    I’m using the version 2 RTL-SDR Blog Active L-Band (before that I was using the version 1 of the antenna) for L-25E and a self made helix antenna and a small dish for L-54W, also of course RTL SDR dongles, Jaero, Raspi’s etc.
    During the last few weeks I wrote a python script for filtering out the different message types (init, wxr, txt etc), the messages are stored in a sqlite database. As a frontend I wrote a small webpage using php and css to display the data in a browser.

    Cheers Roy

    1. Hello Roy!
      Thanks for stopping by.
      Glad you found the site helpful.
      Did I read your comment correctly? You are running Jaero on a Raspberry Pi? If so, I am very interested in hearing more about that. How many Jaeros can you run at the same time on a Pi?
      Sounds like your Python script is doing the same filter work that I am doing in Node-RED.
      The /INI/ and /MC/ reports sure are interesting.
      I am looking to move from MySQL to SQLite, my daily database has around half a million records in it and I am not sure sure what the best (ie, fastest) database is.

      Thanks for your comment. Happy tail-spotting!


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