https://github.com/ps2/omnipod_rf
Experimental python code for decoding omnipod rf packets from SDR
https://github.com/ps2/omnipod_rf
Last synced: about 1 year ago
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Experimental python code for decoding omnipod rf packets from SDR
- Host: GitHub
- URL: https://github.com/ps2/omnipod_rf
- Owner: ps2
- Created: 2016-06-08T17:18:47.000Z (almost 10 years ago)
- Default Branch: master
- Last Pushed: 2016-06-16T01:24:35.000Z (almost 10 years ago)
- Last Synced: 2025-03-29T08:51:13.795Z (about 1 year ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 1.65 MB
- Stars: 9
- Watchers: 0
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Decode Omnipod RF Packets
This repo contains tools for working with raw iq data from an SDR, and will decode the omnipod signal into packets. For more information about the omnipod protocol, see the [omnidocs repo](https://github.com/openaps/omnidocs).
## Prerequisites
* [GNURadio](http://gnuradio.org/), or at least the gnuradio python libraries.
* numpy
## Capturing data
I use [SDR# (SDR Sharp)](http://airspy.com/download/) to capture my iq files, and there are many different ways of doing this. But whatever software you use, you'll need to capture at 2024000 samples per second. *NOTE* While the signal is at 433.923MHz, we don't want to use that as our SDR center, as we will run into center DC noise issues. The code needs to know what offset we're using, so I have dictated an offset of 460kHz. Thus, set your SDR to capture at *433.463MHz*
It should look like this in the end:
Notice that the signal appears to be alternating between two different frequencies. This is [FSK](https://en.wikipedia.org/wiki/Frequency-shift_keying) modulation. If the signal is too weak (the waves are small), move the pod/pdm closer. If the waves are clipped at the top, the signal is too strong.
## Running the decoder
```
$ python omni_decode.py find_pdm.wav
Filename = find_pdm.wav
Using Volk machine: avx_64_mmx
158ms: ffffffffa3ffffffff040607041f01482b037f8d
457ms: ffffffffa3ffffffff040607041f01482b037f8d
756ms: ffffffffa3ffffffff040607041f01482b037f8d
1055ms: ffffffffa3ffffffff040607041f01482b037f8d
1353ms: ffffffffa3ffffffff040607041f01482b037f8d
1652ms: ffffffffa3ffffffff040607041f01482b037f8d
1951ms: ffffffffa3ffffffff040607041f01482b037f8d
2250ms: ffffffffa3ffffffff040607041f01482b037f8d
2549ms: ffffffffa3ffffffff040607041f01482b037f8d
2848ms: ffffffffa3ffffffff040607041f01482b037f8d
3146ms: ffffffffa3ffffffff040607041f01482b037f8d
```