J'ai essayé la modulation AM et la démodulation avec Python. Le démodulateur est GNU Radio AM Demod.
from gnuradio import analog
from gnuradio import audio
from gnuradio import blocks
from gnuradio import eng_notation
from gnuradio import filter
from gnuradio import gr
from gnuradio.eng_option import eng_option
from gnuradio.filter import firdes
from optparse import OptionParser
import sys
import scipy
import numpy as np
import scipy.signal as sg
import pylab
class radio(gr.top_block):
def __init__(self, vam):
gr.top_block.__init__(self)
self.samp_rate = samp_rate = 32000
self.blocks_vector_source_x_0 = blocks.vector_source_f(vam.tolist(), False, 1, [])
self.hilbert_fc_0 = filter.hilbert_fc(65, firdes.WIN_HAMMING, 6.76)
self.blocks_vector_sink_x_0 = blocks.vector_sink_f(1)
self.analog_am_demod_cf_0 = analog.am_demod_cf(channel_rate=32000, audio_decim=1, audio_pass=8000, audio_stop=8100,)
self.connect((self.hilbert_fc_0, 0), (self.analog_am_demod_cf_0, 0))
self.connect((self.blocks_vector_source_x_0, 0), (self.hilbert_fc_0, 0))
self.connect((self.analog_am_demod_cf_0, 0), (self.blocks_vector_sink_x_0, 0))
def main():
sample_rate = 32000.
nsamples = 320
F_1 = 1000.
A_1 = 1.0
F_2 = 10000.
A_2 = 0.5
t = np.arange(nsamples) / sample_rate
vin = A_1 * np.sin(2 * np.pi * F_1 * t)
vam = (A_1 * np.sin(2 * np.pi * F_1 * t) + 1.0) * A_2 * np.sin(2 * np.pi * F_2 * t)
put = radio(vam)
put.run()
data = scipy.array(put.blocks_vector_sink_x_0.data())
f1 = pylab.figure(1, figsize = (12, 10), facecolor = 'w')
s1 = f1.add_subplot(2, 2, 1)
s1.plot(vin)
s3 = f1.add_subplot(2, 2, 2)
s3.plot(vam)
s4 = f1.add_subplot(2, 2, 3)
s4.plot(data)
pylab.show()
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt:
pass
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