Observation 140216: NOAA 15 (25338) I freaking love the high passes!


#1

Regarding Observation 140216

Pleased. Very pleased. :ok_hand:


#2

Especially your wxtoimg picture looks really great!
Do you know, that you can use wxmap to add borders, lakes…


#3

That looks excellent. Nice images


#4

Thank you guys! I’m just trying to autodecode them… I hooked into observer.py – the wrong place to do it. I should recreate a apt.py for wxtoimg. But I don’t understand the whole Satnogs workflow yet…


#5

Yup. Wxmap does it. But I have to check out how the thingydingy works – Satnogs workflow…

EDIT: ogg to wav seems to work… (bad hack).


#6

I have been using wxtoimg and wxmap for a while and have been able to decode and upload the images to satnogs network.

I used a separate python script that does the decoding.

Take a look at these.
https://network.satnogs.org/observations/133541/#tab-data
https://network.satnogs.org/observations/132262/#tab-data
https://network.satnogs.org/observations/132887/#tab-data
https://network.satnogs.org/observations/130461/#tab-data

Tricky part is aligning the maps to the images. Take a look at one of the images.

I have also uploaded to most of my old observations for NOAA.

–JFerns


#7

Hi @Jferns.

Any chance you give an idea how you did it in detail? Or where you hoocked in the wxtoimg tools?

I’m familiar with wxtoimg since years. But with real rx or SDR# only – piping Audio to xwxtoimg or Window$ version of wxtoimg.

But I’m just at the bloody beginning of understanding the Satnogs worklow/snake scripts (.py).


#8

@DE8MSH I avoided making changes in satnogs-client.

Mentioned below are a few details.

I created an offline python script that uses the very good https://network.satnogs.org/api feature and json parsing in python.
Example api call for my station and NOAA 15 https://network.satnogs.org/api/observations/?ground_station=22&norad=25338&format=json
You can use the api and filter for start and end times.

My code is crude but here is the gist.

A python script gets the ogg file path [payload], name and demodulated data[demoddata] from the api.
Observation id, start and end time in the parsed json can be saved and used.
If the number of [payload_demod] entries == 1, meaning a good decoded path and that I have not uploaded decoded data previously, download the ogg file, convert ogg to wav file using sox,

Wxmap requires tle data for the day and time the actual observation took place. I used requests to get this from the observation page directly and using regrex to find the correct tle data (https://network.satnogs.org/observations/134986/) . I would have liked to use the jobs/ api to get the TLE for the observation but currently satnogs jobs api only supports future observations. The tle data was saved as a file tle.txt and used with wxmap

The generated map file is easy to use with wxtoimg. The wxtoimg generated files were then moved to /tmp/.satnogs/data/ on the raspberry pi. Name structure is crucial or else satnogs-client will not upload the files.

wxmap, wxtoimg, sox commands were run using the os.system() in python.

I could automate a majority of the steps above. I also check for average system load (less than 50% out of 400%) before each step to make sure the raspberry pi is not busy with other important tasks like gnuplot for example.

A good reference would be https://github.com/deckbsd/glouton-satnogs-data-downloader for the api and json stuff.

Hope this helps,
Jferns


#9

Hi @Jferns.

Thank you very much! This gives me a very good idea how you did it. Great job!!!


#10

Just interestinged in how you got wxtoimg to actually make images from your sound files. When I pass the audio file from observations of mine that Satnogs has Images for wxtoimg refuses to generate them.

Unless it has to do with how I converted my .ogg to .wav


#11

are you using a preliminary pass like for example:
sox satnogs/satnogs_143938_2018-05-25T17-45-55.ogg -r 11025 satnogs/satnogs_143938_2018-05-25T17-45-55.wav

I think wxtoimg refuses to work without wav of 11025Hz sampling freq.


#12

You can see my house on that picture (and every other house I have ever lived in)!

I’m a new user and these are the sort of results I am aspiring to. Thanks for sharing!