mckero
78a6f270bf
The operator reported that any tone leaked across the whole display - "even 3 kHz spreads
over the entire band, like taking a piss". The tone shifter was the suspect, since it had
been changed recently. It turned out to be innocent: the audio reaching it was already
ruined.
Capture runs at 44100 Hz and the model needs 3200 Hz, so resampleLinear decimates by a
factor of nearly 14. It interpolates between samples and nothing removes the content above
the new Nyquist of 1600 Hz first, which is the one thing decimation cannot skip. Measured on
44100 Hz input:
3000 Hz tone -> ghost at 200 Hz, 119x the spectral mean
2400 Hz tone -> ghost at 800 Hz
1800 Hz tone -> ghost at 1400 Hz
5000 Hz tone -> ghost at 1400 Hz
Each ghost is as strong as a real signal, so a tone nothing is transmitting on looks
entirely convincing. Worse for actually copying anything: the whole 1600-22050 Hz band of
hiss folds down on top of the signal and lifts the noise floor across the display. That is
the smearing.
CwAntiAlias is a 127-tap windowed-sinc low-pass, Blackman-windowed because sidelobe level is
what decides how much of the folded band survives, cut off at 92% of the target Nyquist so
the transition lands inside the discarded region. Measured suppression at the fold
frequency: 2400 Hz down 69 dB, 3000 Hz down 81 dB, 5000 Hz down 96 dB. 1800 Hz only makes
16 dB - it sits just past the 1472 Hz cut-off and 127 taps cannot be steeper without costing
more time than a phone has during a pass. The tests assert the measured numbers rather than
the ones I hoped for.
resampleLinear itself is untouched. Its comment notes it matches the reference implementation
DeepCW was trained against, so changing its arithmetic would move the spectrogram away from
what the model expects.
The streaming path holds output back by the group delay. A first attempt let the lookahead
taps read zeros at the end of each chunk, which diverged from whole-buffer filtering by
0.134 across the last 44 samples of every chunk - a click at each boundary. Holding output
back makes the two identical to within 1e-8. The cost is 63 samples, 1.4 ms, against a 20 WPM
dot of about 60 ms.
Both the decoder and the waterfall filter now. The waterfall mattered as much as the
decoder: it was showing the folded spectrum, which is what the operator was looking at.
Look4Sat: Satellite tracker
Radio satellite tracker and pass predictor for Android, inspired by Gpredict
Track satellite passes with ease!
Thanks to Celestrak and SatNOGS you have access to over 9000 active satellites.
You can search the entire database by NORAD Catalog Number or the satellite's name.
Orbital positions and passes are calculated relative to your location.
To get reliable data make sure to set the station position via the app Settings.
The application is built using Kotlin, Coroutines, Jetpack Compose and Navigation.
It is now and always will be completely ad-free and open-source.
Main features:
- Predicting satellite positions and passes for up to 10 days
- Showing the list of currently active and upcoming satellite passes
- Showing the active pass progress, polar trajectory and transceivers info
- Showing the satellite positional data, footprint and ground track on the map
- Custom TLE satellite data import is available via Three Line Element .txt files
- Offline first: calculations are made offline. Weekly TLE data update is recommended.
License
The Look4Sat application code is licensed under the GNU General Public License v3.0.
The CW decoder in feature/cw bundles the DeepCW
neural decoding model, licensed under the GNU Affero General Public License v3.0 only
(AGPL-3.0-only). Because the combined work incorporates an AGPL-3.0 component, the
combined work is distributed under the
GNU Affero General Public License v3.0 — GPL-3.0 Section 13 permits the
combination, and AGPL-3.0 Section 13 applies to the combined work as a whole.
Model provenance and attribution are documented in
feature/cw/licenses/NOTICE.md; the original GPL-3.0
text is preserved at feature/cw/licenses/Look4Sat-GPL-3.0.txt. The CW model runs
locally on-device and does not provide services over a network.