Baseband Cuts
One isolated, baseband, time-cut signal per file — each with a metadata label. The clean, balanced examples a classifier trains on.
Open the generatorOne signal per file, cleanly labeled.
Each message is rendered to baseband and cut to its own file — no receiver tune, no other signals, no overlap. Multi-burst messages stay together as one cut. Every file ships with a metadata record of the exact parameters that produced it.
The simplest case — one signal, isolated at baseband.
A modulated message, cut to its own file and labeled.
Set a range and every cut is drawn independently.
The library spans generic modulations and the real over-the-air protocols built on them — framing, coding and payloads included, not just a carrier with the right shape. It grows continuously; the generator always lists what's available now.
Give a field a range (0.05–0.2) or a set (2,4,8) and it's sampled per signal — large, varied datasets, hands-off.
Add the flaws a real front end introduces — carrier and clock offset, phase noise, IQ imbalance, DC bias. Train on signals that look like the ones you'll actually receive, not just clean ones.
Export raw IQ or spectrograms in many common formats.
From blank form to labeled zip.
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1
Add signals and set parameters
Add one or more modulations and dial in sample rate, noise, and per-signal options. Use ranges to randomize.
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2
Set how many
Choose a signal count — each one becomes its own independently-drawn, isolated file.
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3
Pick an output format
Choose raw IQ or spectrogram images, and the file format for your pipeline.
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4
Generate and download
Export a zip where every file carries a metadata record of the exact parameters that produced it.