1. AMSAT SA SPACE SYMPOSIUM 2019 Author :Anton Janovsky ZR6AIC
How to use AI (Artificial Intelligence) to identify Radio signals using a RTL SDR dongle and Linux (Ubuntu)
AMSAT SA SPACE SYMPOSIUM 2019
Author :Anton Janovsky ZR6AIC

2. AMSAT SA SPACE SYMPOSIUM 2019
Selecting the Best used AI framework
Here is a graph with all the most used Deep learning frameworks available.
AMSAT SA SPACE SYMPOSIUM 2019
HackRF
RaspberryPi
RTL Dongle

3. AMSAT SA SPACE SYMPOSIUM 2019
Background of AI
How to use AI (Artificial Intelligence) to identify Radio signals using a RTL SDR dongle and Linux (Ubuntu)
I was wondering if there is not a good framework to identify RF signals as I wanted to add some capabilities to my SDR's to identify RF signal.
I was thinking of a way to recognize Satellite signals and the automatically apply the necessary Demodulator's and decoders for the specific satellite.
I was looking at AI Deep Learning library to be able to identify RF Radio signals. There are countless deep learning frameworks available today.
By using Python3 and rtl-sdr dongle it would be possible to scan a frequency range trying to identify a satellite.
AMSAT SA SPACE SYMPOSIUM 2019

4. AMSAT SA SPACE SYMPOSIUM 2019
Hardware.
Google Cloud
Tenserflow
AMSAT SA SPACE SYMPOSIUM 2019
HackRF
RaspberryPi
RTL Dongle

5. Deciding how to go from here.
I found this open source project called cnn-rtlsdr and it is available from github here
This framework is using Keras and TensorFlow to learn and recognize the RF signals.
So how does it work?
You first need take an clean RF signal and digitize it and then let the framework learn its signature. The more you letting the AI framework learn a specific signal the more accurate it will able to recognize the RF Signal.
AMSAT SA SPACE SYMPOSIUM 2019

6. AMSAT SA SPACE SYMPOSIUM 2019
Installing and setting up
Let's check if you have version 2 or 3 of python.
You need version 3
python -V
apt-get install git
git clone
cd cnn-rtlsdr
sudo apt-get update
sudo apt-get install python3-pip
sudo apt-get install rtl-sdr
sudo apt-get install build-essential libssl-dev libffi-dev python-dev
sudo pip3 install --upgrade pip
sudo pip3 install tensorflow
sudo pip3 install pyrtlsdr
sudo pip3 install scipy
[remove dongle]
rmmod dvb_usb_rtl28xxu rtl2832
[insert dongle]
AMSAT SA SPACE SYMPOSIUM 2019

7. AMSAT SA SPACE SYMPOSIUM 2019
Installing and setting up
sudo apt-get install automake
sudo apt-get install libtool
sudo apt-get install libfftw3–dev
sudo apt-get install librtlsdr-dev
sudo apt-get install libusb1.0.0-dev
AMSAT SA SPACE SYMPOSIUM 2019

8. AMSAT SA SPACE SYMPOSIUM 2019
Let’s test to see if we can identify any signals
sudo python3 predict_scan.py
Found Rafael Micro R820T tuner
[R82XX] PLL not locked!
MHz - tv 99.98%
MHz - tv 99.91%
MHz - tv 99.99%
MHz - tv 99.93%
MHz - tv 99.13%
MHz - tv 98.04%
MHz - tv %
MHz - tv 99.95%
MHz - tv 81.13%
MHz - tv 99.91%
MHz - tv %
MHz - tv %
MHz - tv 99.56%
AMSAT SA SPACE SYMPOSIUM 2019

9. AMSAT SA SPACE SYMPOSIUM 2019
Let’s test to see if we can identify any signals.
We now need to learn the different Rf signals so we can identify it.
Best way to do this is with an rtl dongle and your signal of interest.
Learning from existing RF signal Database.
1) "wfm" Wide band FM
2) "tv" TV signal
3) "gsm" GSM signal
4) "tetra" Tetra DMR
5) "dmr" DMR
5) "other"
AMSAT SA SPACE SYMPOSIUM 2019

10. AMSAT SA SPACE SYMPOSIUM 2019
Get existing DB that already lerd rf signals
Link to database
Some RF signals have been learned by other users so you don't need to learn the common RF signals but just import the learn database.
Unzip the file in the cnn-rtlsdr directory
Then run the following command to learn the RF signal
It takes about 80secons to learn a sample. So go and have a coffee or a bear :-)
Make sure you have your rtl_sdr dongle connected as the code will do a test at the end of the learning procedure.
python3 train_keras.py
You will need a lot of memory for your application to run so close all necessary applications otherwise you will get an out of memory error.. ( usef 500Mb in now time so I recommend using External hard drive)
AMSAT SA SPACE SYMPOSIUM 2019

11. Learning my own unique signal.
python3 train_keras.py
Using TensorFlow backend.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1062: calling reduce_prod (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:2550: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1123: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Train on samples, validate on samples
Epoch 1/50
64972/64972 [==============================] - 70s - loss: acc: val_loss: val_acc:
Epoch 2/50
64972/64972 [==============================] - 72s - loss: acc: val_loss: val_acc:
...
64972/64972 [==============================] - 79s - loss: acc: val_loss: val_acc:
Epoch 49/50
64972/64972 [==============================] - 80s - loss: e-04 - acc: val_loss: val_acc:
Epoch 50/50
64972/64972 [==============================] - 78s - loss: acc: val_loss: val_acc:
AMSAT SA SPACE SYMPOSIUM 2019

12. Identifying using my own Database
Found Rafael Micro R820T tuner
[R82XX] PLL not locked!
92.9 wfm
49.25 other
95.0 other
104.0 other
422.6 other
100.5 other
120.0 other 100.0
106.3 wfm 100.0
942.2 other
107.8 other 100.0
Validation: 30.0
AMSAT SA SPACE SYMPOSIUM 2019

13. AMSAT SA SPACE SYMPOSIUM 2019
Questions?
Complete details is available from my Blog
AMSAT SA SPACE SYMPOSIUM 2019