LoginSignup
5
3

More than 5 years have passed since last update.

PythonでFM変調、復調 その2

Last updated at Posted at 2017-01-25

概要

PythonでFM変調、復調してみた。
復調アルゴリズムは、googleラジオ

写真

figure_1.png

サンプルコード

import scipy.signal as sg
import numpy as np
import matplotlib.pyplot as plt

sample_rate = 48000.0
nsamples = 320
F_1 = 440.0
F_2 = 10000.0
F_3 = 10000.0
nyq_rate = sample_rate / 2.0
cutoff_hz = 5000.0
numtaps = 29
t = np.arange(nsamples) / sample_rate
vin = np.sin(2 * np.pi * F_1 * t) 
vfm = np.sin(2 * np.pi * F_2 * t + 6.0 * -np.cos(2 * np.pi * F_1 * t))
i1 = vfm * np.cos(2 * np.pi * F_3 * t)
q1 = vfm * np.sin(2 * np.pi * F_3 * t)
lpf = sg.firwin(numtaps, cutoff_hz / nyq_rate)
I2 = sg.lfilter(lpf, 1, i1)
Q2 = sg.lfilter(lpf, 1, q1)
pI = 0
pQ = 0
m = 0
vo = np.zeros(320)
for t in range(0, vfm.size):
   real = pI * I2[t] + pQ * Q2[t]
   imag = pI * Q2[t] - pQ * I2[t]
   sgn = 1
   circ = 0
   ang = 0
   div = 1
   if (real < 0):
      sgn = -sgn
      real = -real
      circ = np.pi
   if (imag < 0):
      sgn = -sgn
      imag = -imag
      circ = -circ
   if (real > imag):
      div = imag / real
   else:
      if (real != imag):
         ang = -np.pi / 2
         div = real / imag
         sgn = -sgn
   vo[t] = circ + sgn * (ang + div / (0.98419158358617365 + div * (0.093485702629671305 + div * 0.19556307900617517))) * 5
   pI = I2[t]
   pQ = Q2[t]
fig = plt.figure(1)
ax = fig.add_subplot(311)
ax.plot(vin[1:300])
ax = fig.add_subplot(312)
ax.plot(vfm[1:300])
ax = fig.add_subplot(313)
ax.plot(vo[1:300])
fig.set_tight_layout(True)
plt.show()



5
3
0

Register as a new user and use Qiita more conveniently

  1. You get articles that match your needs
  2. You can efficiently read back useful information
  3. You can use dark theme
What you can do with signing up
5
3