Wouldn’t it be fun if you could see electromagnetic waves by yourself? Now you can, by turning a Pluto radio into a spectrum analyzer that sweeps anything from 100 MHz to 6 GHz, all you need is a little bit of technical know-how and some patience.
Indeed, using the system’s lock-in amplifier technique and the straightforward Python code, you can scan all frequencies and observe electromagnetic activity, including WiFi, Bluetooth, radio systems, both commercial and amateur, and even cell phones.
And the best part? You’ll also be able to detect anomalies that could indicate hidden transmitters in your surroundings.
As it happens, an engineer known as ‘From Concept to Circuit’ has devised a way to do just that using an ADALM Pluto SDR turned into a real-time Spectrum Analyzer using Python and PyQt, explaining the whole process in a YouTube video and on GitHub, alongside code and all the necessary tools.
How to ‘see’ electromagnetic waves
To begin, the engineer needed several things – ADALM Pluto SDR (software-defined radio active learning module), Python 3 code, PyQt6 (GUI framework), PyQtGraph (for real-time graph plotting), as well as NumPy and SciPy (for signal processing and filtering).
Now, it was time to put all these into action. First of all, you need to clone the repository:
| git clone https://github.com/fromconcepttocircuit/ADALM-Pluto-Spectrum-Analyzer.git cd ADALM-Pluto-Spectrum-Analyzer |
Then, install the required Python libraries:
| pip install pyadi-iio numpy scipy pyqt6 pyqtgraph |
If you’re a Linux user, install an additional system package to avoid missing Qt plugin errors:
| sudo apt install libxcb-cursor-dev |
Now, run the spectrum analyzer:
| python spectrum_analyzer.py |
Finally, connect ADALM Pluto SDR, making sure it is reachable at its default IP: 192.168.2.1, adjusting the IP address in the code if necessary:
| self.sdr = adi.ad9361(uri=’ip:192.168.2.1′) |
You’ll need to adjust sweep and settings in GUI, including adjusting sample rate (Hz), setting filter cutoff frequency (Hz), sweep start/stop or the frequency range to scan (Hz), resolution of the sweep (# of points), dB threshold to trigger alerts, and peak hold/markets to analyze signals in detail. The GUI may also require PyQt6-specific themes for proper visualization.
Conclusion
And there you have it – your very own real-time electromagnetic wave spectrum analyzer is ready for you to put to good use and make the invisible visible. If you’re up to some other cool projects, why not try making your own GPS receiver, ‘glasses’ that transcribe text to audio for the blind, or a plasma tube from a kombucha bottle? The possibilities are endless.
