Studying the Ionospheric Radio Signals Propagation Using Python and SDR

Studying the Ionospheric Radio Signals Propagation Using Python and SDR

Studying the Ionospheric Radio Signals Propagation Using Python and SDR. I will show, how using an SDR receiver and 50 lines of Python code, it is possible to visualize radio stations signals with <0.01 Hertz accuracy and observe some interesting atmospheric effects.

Readers who were born at the 70s or earlier, and had medium-, long- or shortwave receivers at home, probably remember that stations of different wavelengths propagate differently at different times of the day. But how does it really work?

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I will show, how using an SDR receiver and 50 lines of Python code, it is possible to visualize radio stations signals with <0.01 Hertz accuracy and observe some interesting atmospheric effects.

General Idea

Most AM radio stations are broadcasting 24h per day, which allows us to analyse the radio signals they transmit. To do this, we will record the radio signal in WAV format and plot its spectrum using FFT (Fast Fourier Transform). FFT makes it possible to obtain an image in the frequency domain from a signal in the time domain, in other words, to get a spectrum of the signal. The larger the FFT window, the more frequency resolution we can get.

As we know, the signals of AM stations on the air look like this:

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The actual broadcast content is not interesting to us (is anyone still listening to the radio nowadays?), but the AM carrier — the centre of the signal, is important. It is a good marker by which it is convenient to monitor the signal on the spectrum.

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