- See HamSCI Sunrise Festival Page for the details
- See also wwv-h-wg GitHub repository for the analysis by Jupyter Notebook
- Linux (tested on Ubuntu 21.10 and 22.04) (May work on macOS but not tested)
- Airspy HF+ Tools
- Advanced Python Scheduler
- sox (available on Ubuntu and macOS Homebrew)
- Specify the working directory with the variable
recorddir
ofsunrisefest-recording.py
- Change other initial settings
- Put
record-airspyhf.sh
in the working directory - Put
sunrisefest-recording.py
in the working directory - Chdir to the working directory
- Run
./sunrisefest-recording.py
- The script runs the recording jobs on every 8 and 48 minutes of the hour
- Running this under a tmux window or a typescript process is convinient for the logging
- You will find a list of recorded files in the working directory
UTC: 2022-04-14 07:08:00.005203
Receive WWVH for JJ1BDX_WWV_10MHz_2022-04-14_07-08.wav
Device Serial Number: 0x3652A980E9C746F7
Stop with Ctrl-C
User cancel, exiting...
Total time: 60.2846 s
Average speed 0.1920 MS/s IQ
done
UTC: 2022-04-14 07:48:00.004328
Receive WWVH for JJ1BDX_WWVH_10MHz_2022-04-14_07-48.wav
Device Serial Number: 0x3652A980E9C746F7
Stop with Ctrl-C
User cancel, exiting...
Total time: 60.2848 s
Average speed 0.1920 MS/s IQ
done
- 24ksamples/sec (24kHz) stereo (IQ) 32-bit float WAV
- The WAV files can be directly monitored with various audio recording software including AudaCity and Fission
- Normalize the sound file before listening to it with your ears
- You can use airspy-fmradion to listen to the files too
- A command example:
airspy-fmradion -t filesource -m am -c freq=10000000,filename=JJ1BDX_WWVH_10MHz_2022-04-14_07-48.wav -P -
- A command example:
Because it's accurate and the jobs are turned on in within <10msec of the scheduled time. Cron is not this accurate.
MIT