mckero
9798107d37
DeepCW only analyses 400-1200 Hz - its input tensor is 65 bins wide, fixed at training time - so a CW note outside that range is invisible to the decoder. This adds an opt-in preprocessing step that moves such a tone to 800 Hz, the window centre, extending the usable pitch range without touching the model. Single-sideband mixing via a 63-tap Hilbert transformer. Plain real mixing was measured and rejected: shifting 1500 Hz to 800 Hz left a fold-back image at 1000 Hz at 0.999 of the wanted amplitude, inside the window. Zero-stuff upsampling plus lowpass handled downward shifts but left a 0.996 image when shifting 300 Hz upward. The Hilbert approach measures clean on nine tones from 150 to 1550 Hz: one peak at the target, nothing above 0.3 relative amplitude. In-window energy for a 1500 Hz input goes from 6.8% to 94.6%. Only out-of-range audio is processed. A tone already inside 400-1200 Hz is returned untouched (same array instance, no copy), and with the setting off the audio path is exactly what it was before. CwToneShifter.Streaming carries the Hilbert filter history and mixer phase across capture chunks. Shifting each chunk in isolation left 62 of every 320 samples convolving against zeros, inflating envelope ripple to 8.7x the whole-buffer baseline. A residual difference in the last ~3 samples of each chunk is causal and documented: those output samples would need input that has not been captured yet. Detection pools chunks rather than gating on one. A capture chunk is 4410 samples at 44.1 kHz but only 320 after resampling to 3200 Hz, so requiring 1280 samples in a single chunk would have made the feature dead code - the two independent audits both found this before it shipped. Detection now runs on a pooled 0.4 s window, at most every 2 s. Toggling the setting or a change in the detected shift drops the buffered audio: the 20 s window would otherwise keep decoding samples moved by the old amount, and the pitch readout could only be correct for one of them. The readout itself subtracts the active shift so it shows the pitch on the radio, not the shifted one. Settings: OtherSettings.cwToneShiftEnabled, off by default, persisted and read back in SettingsRepo, toggled from the Other card in Settings with a help line explaining the 400-1200 Hz limit. Strings added to all nine locales. The decoder reads the flag per chunk, so the toggle applies without restarting capture. Debug: the enabled-state transition, each detection verdict (no tone / inside window / shifting by N Hz), and every shift change are logged, with the noisy paths throttled to the 2 s detection interval. CwProbe records shift changes only, keeping well inside its 1 MiB cap. Tests: 8 shifter tests (detection sweep, noise rejection, pass-through identity, image-free shifting across 8 tones, end-to-end spectrogram energy), 8 streaming tests (chunk continuity, history retention, reset semantics, chunk sizes above and below the history window), and 6 gate tests including a regression guard that a 320-sample chunk must be able to reach the detection threshold. All 53 CW tests pass, golden vectors included.
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.