Year Review 2022

Wrote up the results of poking around the corpus of observations data and ground stations. That same database is used to generate other summary plots generated in this Jupyter notebook

Main link:

Table of Contents to see if it may contain anything of interest to you:

The most surprising things to me:

  • There are only 2 ground stations with azimuth-only rotators (that I can tell). IMO this is the sweet spot for performance versus cost and maintenance. An analysis showing this is on my “middle burner.”

Other stats:

  • 77% of Online or Testing stations have no rotator.
  • turnstile, yagi, and quadrafilar antenna types are the top three most popular
  • NOAA-{18, 19, 15}, METEOR M-2, and the ISS were among the most popular satellites.

Just writing this post, I’ve thought of many more summary statistics to compute that aren’t in there. Having a local SQLite database makes querying feasible (most took < 4 s) compared to hitting the APIs — I’m happy to give a copy (~1.8 GB gzipped) to anyone who asks.

What statistics would you find interesting?


Excellent, still trying to find a way to find the best GS (most sensitive) for searching those “dead” satellites still showing life!

  1. Best antenna
  2. Lowest noise/interference
  3. Best NF

Have a look at the stations that tops the list here, sort by data.
Also at the main page under recent contributors, check what those stations are running.
For UHF omni I nominate QFH with feedpoint LNA.
For VHF/UHF directional I nominate X-yagi (rhcp) with LNA.
Regarding LNA, almost any will make a decent improvement against using none, I nominate PGA103+.


Good choices! I am actually looking for objective analysis, using the data captured over time to see what stations actually see satellites transmitting very low power, of course high gain tracking antennas are the best. Also which stations, maybe not in a city, have less interference and can actually decode data even at low elevations. Would be a nice challenge, instead of chasing qty, to see who has the optimal GS on satnogs :wink:

@jjroux I’m looking for help with that work :wink: . The enduring value I think, is scripting the analysis so it is easy to update over time. Otherwise it’s a (useful!) point measurement.

A goal is to document what actually works well from the data, then put those practices into a kit. Such work is happening in places like satnogs-kit and satnogs-webgui. It’s the analysis itself that’s not well documented

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Good work.

I also think we will be able to get some of the satellites GS (where they have uplinks) looking at amount of data they download in certain areas!

Anyway statistics gathering is a huge work

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