Finalize demod

1 files changed, 42 insertions, 4 deletions

diff --git a/numpy_fm_demod.py b/numpy_fm_demod.py
index fb2c46b..44d232d 100644
--- a/numpy_fm_demod.py
+++ b/numpy_fm_demod.py
@@ -10,7 +10,7 @@ class NumpyFmDemod():
     Based on the great tutorial by Fraida Fund
     https://witestlab.poly.edu/blog/capture-and-decode-fm-radio/
     '''
-    def __init__(frequency, sample_rate=1140000, sample_count=8192000, dc_offset=250000):
+    def __init__(self, frequency, sample_rate=1140000, sample_count=8192000, dc_offset=250000):
         self.freq = int(frequency)
         self.sample_rate = sample_rate
         self.sample_count = sample_count
@@ -21,12 +21,50 @@ class NumpyFmDemod():
         sdr.sample_rate = self.sample_rate
         sdr.center_freq = self.freq - self.dc_offset
         sdr.gain = 'auto'
-
-        samples = sdr.read_samples(self.sample_count)
+        self.samples = sdr.read_samples(self.sample_count)
         sdr.close()
 
-        self.raw_samples = np.array(samples).astype('complex64')
+    def demod(self):
+        # Convert samples to a numpy array
+        x1 = np.array(self.samples).astype('complex64')
+
+        # Mix the samples back down to avoid DC offset
+        fc1 = np.exp(-1.0j * 2.0 * np.pi * self.dc_offset / self.sample_rate * np.arange(len(x1)))
+        x2 = x1 * fc1
+
+        # Downsample the signal to catch only the target frequency
+        BANDWIDTH = 200000  # wideband FM signal is always 200kHz
+        TAPS = 64
+
+        # Use Remez algorithm to design filter coefficients
+        lpf = signal.remez(TAPS, [0, BANDWIDTH, BANDWIDTH + (self.sample_rate / 2 - BANDWIDTH) / 4, self.sample_rate / 2], [1,0], Hz=self.sample_rate)
+        x3 = signal.lfilter(lpf, 1.0, x2)
+
+        decimation_rate = int(self.sample_rate / BANDWIDTH)
+        x4 = x3[0::decimation_rate]
+        decimated_rate = self.sample_rate / decimation_rate
+
+        y5 = x4[1:] * np.conj(x4[:-1])
+        x5 = np.angle(y5)
+
+        d = decimated_rate * 75e-6  # Calculate the # of samples to hit the -3dB point
+        x = np.exp(-1/d)  # Calculate the decay between each sample
+        b = [1-x]  # Create the filter coefficients
+        a = [1,-x]
+        x6 = signal.lfilter(b,a,x5)
+
+        audio_freq = 44100.0
+        dec_audio = int(decimated_rate / audio_freq)
+        Fs_audio = decimated_rate / dec_audio
+
+        x7 = signal.decimate(x6, dec_audio)
+
+        x7 *= 10000 / np.max(np.abs(x7))
+        x7.astype('int16').tofile('wbfm-mono.raw')
 
+    def run(self):
+        self.capture_samples()
+        self.demod()
 
 if __name__ == '__main__':
     nfd = NumpyFmDemod(frequency=96.3e6)