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This talk¶
- I never learned physics, RF engineering or signal processing
- But radios are pretty cool! @@ -11934,59 +14693,77 @@ a.anchor-link {
- Slides and code @ https://github.com/yuvadm/radio-pyconil-2018
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Radio¶
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Hardware Radio¶
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Hardware Radio¶
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Software-Defined Radio¶
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What's it good for¶
- Digital TV broadcast ("Idan+", DVB-T)
- Airplane tracking (ADS-B) @@ -11995,83 +14772,107 @@ a.anchor-link {
- FM radio broadcast
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Airplane Location Tracking (ADSB)¶
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Weather Satellites¶
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GQRX¶
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# pyrtlsdr provides us bindings to work with the RTL-SDR driver
-from rtlsdr import RtlSdr
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sdr = RtlSdr()
sdr.sample_rate = 1.2e6 # 1,200,000 samples per second
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sdr.close()
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# Alternatively, load previously captured samples from rtl_sdr
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samples = (raw[0::2] + 1j * raw[1::2]).astype(np.complex64)
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# We captured too many samples so we need to apply a low pass filter
# In other words, we have a too large window and we want to make it smaller
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samples = signal.decimate(samples, DECIMATION_RATE)
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# Apply the Frequency DEmodulation
# We use something called a polar discriminator
samples = np.angle(samples[1:] * np.conj(samples[:-1]))
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# De-emphasis filter
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samples = signal.lfilter(b, a, samples)
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# Decimate the signal down to something an audio driver can handle
# We only catch the mono part of the signal
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samples = samples.astype('int16')
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# HIT IT
import alsaaudio
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device.write(s)
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Review¶
- Took a fixed set of samples, did some math on them
- Python, NumPy and SciPy are very good at doing fast processing of static data @@ -12227,13 +15049,16 @@ a.anchor-link {
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GNU Radio¶
- Comprehensive signal processing framework
- Implemented many DSP primivites @@ -12241,13 +15066,16 @@ a.anchor-link {
- Actually generates flowgraphs in Python