# CTCSS fingerprinting: a method for transmitter identification

DevFeed: [CTCSS fingerprinting: a method for transmitter identification](<https://devfeed.tech/articles/ctcss-fingerprinting-a-method-for-transmitter-identification-21647.md>)

Original publisher: [Read original article](<https://www.windytan.com/2016/10/ctcss-fingerprinting-method-for.html>)

Author: Oona Räisänen (noreply@blogger.com)

Published: 2016-10-07T13:17:00Z

Content type: article

Language: en

Sources: [Oona Räisänen](<https://devfeed.tech/sources/oona-raisanen.md>)

Topics: [Programming](<https://devfeed.tech/topics/programming.md>), [Streams](<https://devfeed.tech/topics/streams.md>), [Library](<https://devfeed.tech/topics/library.md>), [USB](<https://devfeed.tech/topics/usb.md>)

Tags: [algorithms](<https://devfeed.tech/tags/algorithms.md>), [analysis](<https://devfeed.tech/tags/analysis.md>), [audio](<https://devfeed.tech/tags/audio.md>), [communications](<https://devfeed.tech/tags/communications.md>), [dsp](<https://devfeed.tech/tags/dsp.md>), [library](<https://devfeed.tech/tags/library.md>), [quality](<https://devfeed.tech/tags/quality.md>), [radio](<https://devfeed.tech/tags/radio.md>), [security](<https://devfeed.tech/tags/security.md>), [side-channels](<https://devfeed.tech/tags/side-channels.md>), [signal](<https://devfeed.tech/tags/signal.md>), [usb](<https://devfeed.tech/tags/usb.md>), [voice](<https://devfeed.tech/tags/voice.md>), [walkie-talkie](<https://devfeed.tech/tags/walkie-talkie.md>)

## AI overview

The article investigates whether the 88.5 Hz CTCSS tone in hand-held FM transceivers can fingerprint transmitters by revealing small differences in crystal frequencies and modulation depths. It describes analyzing walkie-talkie recordings with liquid-dsp and a phase-locked loop.

## Source excerpt

Identifying unknown radio transmitters by their signals is called radio fingerprinting. It is usually based on rise-time signatures, i.e. characteristic differences in how the transmitter frequency fluctuates at carrier power-up. Here, instead, I investigate the fingerprintability of another feature in hand-held FM transceivers, known as CTCSS or Continuous Tone-Coded Squelch System. Motivation & data I came across a long, losslessly compressed recording of some walkie-talkie chatter and wanted to know more about it, things like the number of participants and who's talking with who. I started writing a transcript - a fun pastime - but some voices sounded so similar I wondered if there was a way to tell them apart automatically. The file comprises several thousand short transmissions as FM demodulated audio lowpass filtered at 4500 Hz. Signal quality is variable; most transmissions are crisp and clear but some are buried under noise. Passages with no signal are squelched to zero. I considered several potentially fingerprintable features, many of them unrealistic: Carrier power-up; but many transmissions were missing the very beginning because of squelch Voice identification; but it would probably require pretty sophisticated algorithms (too difficult!) and longer samples Mean audio power; but it's not consistent enough, as it depends on text, tone of voice, etc. Maximum audio power; but it's too sensitive to peaks in FM noise I then noticed all transmissions had a very low tone at 88.5 Hz. It turned out to be CTCSS, an inaudible signal that enables handsets to silence unwanted transmissions on the same channel. This gave me an idea inspired by mains frequency analysis: Could this tone be measured to reveal minute differences in crystal frequencies and modulation depths? Also, knowing that these were recorded using a cheap DVB-T USB stick - would it have a stable enough oscillator to produce consistent measurements? Measurements I used the liquid-dsp library for signa