Merge pull request #428 from alanbjohnston/fiabv4-auto-tune-p
Pi 4 Changes and Other PacSat Fixesmaster-b
Alan Johnston
5 days ago
committed by
GitHub
commit
b55fdec26e
@ -0,0 +1,93 @@
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from rtlsdr import RtlSdr
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import numpy as np
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import matplotlib.pyplot as plt
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import sys
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if __name__ == "__main__":
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graph = 'n'
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center_frequency = 434.7e6
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if (len(sys.argv)) > 0:
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# print("There are arguments!")
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center_frequency = float(sys.argv[1]) - 200e3
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if (center_frequency == 0):
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center_frequency = 434.7e6
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if (len(sys.argv)) > 1:
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# print("There are more arguments")
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if (sys.argv[2] == 'g') or (sys.argv[2] == '-g'):
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graph = 'y'
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sampling_rate = 1024e3 # 250e3 # Hz
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duration = 65536/sampling_rate # 1 # seconds
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try:
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sdr = RtlSdr()
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# configure device
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sdr.sample_rate = sampling_rate # 250e3 # 2.4e6
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#center_frequency = 434.8e6
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sdr.center_freq = center_frequency
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sdr.gain = 47
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sdr.direct_sampling = False
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# signal = sdr.read_samples(64*1024) #256
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signal = sdr.read_samples(duration*sampling_rate).real #256
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# print(f"Center frequency is {center_frequency}")
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sdr.close()
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# Compute the FFT
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fft_result = np.fft.fft(signal)
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# Calculate the frequencies corresponding to the FFT output
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n = len(signal)
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frequencies = np.fft.fftfreq(n, d=1/sampling_rate)
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# Take the absolute value for amplitude spectrum and consider only the positive frequencies
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positive_frequencies_indices = np.where(frequencies >= 0)
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positive_frequencies = frequencies[positive_frequencies_indices]
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amplitude_spectrum = 2/n * np.abs(fft_result[positive_frequencies_indices]) # Normalize for amplitude
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if (graph == 'y'):
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# Plotting the results
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t = np.linspace(0, duration, int(sampling_rate * duration), endpoint=False)
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plt.figure(figsize=(12, 6))
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plt.subplot(1, 2, 1)
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plt.plot(t, signal)
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plt.title('Time Domain Signal')
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plt.xlabel('Time (s)')
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plt.ylabel('Amplitude')
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plt.subplot(1, 2, 2)
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plt.stem(positive_frequencies, amplitude_spectrum, markerfmt=" ", basefmt="-b")
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plt.title('Frequency Domain (FFT)')
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plt.xlabel('Frequency (Hz)')
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plt.ylabel('Amplitude')
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plt.grid(True)
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plt.tight_layout()
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plt.show()
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# print(amplitude_spectrum)
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x = amplitude_spectrum
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# print(x)
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min_value = min(x)
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max_value = max(x) * 100
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#freq_min = np.argmax(min_value)
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# print(np.argmax(x))
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# print(np.argmax(x)*(150e3 - 10e3)/(9770 - 709))
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# print(sampling_rate)
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# print(center_frequency)
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offset = (np.argmax(x)*(150e3 - 10e3)/(9770 - 709))
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freq_max = center_frequency + offset + 2000
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except: # if no RTL-SDR or in use, stop scanning with high max value and center frequency
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max_value = 100
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freq_max = center_frequency + 200e3 # should be 434900000
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print(f" {freq_max:.0f} {max_value:.0f}")
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