Adding a time sync class with an implementation of the M&M algorithm #24

spacelab_decoder/time_sync.py

@@ -0,0 +1,72 @@
+# -*- coding: utf-8 -*-
+
+#
+#  time_sync.py
+#  
+#  Copyright The SpaceLab-Decoder Contributors.
+#  
+#  This file is part of SpaceLab-Decoder.
+#
+#  SpaceLab-Decoder is free software; you can redistribute it
+#  and/or modify it under the terms of the GNU General Public License as
+#  published by the Free Software Foundation, either version 3 of the
+#  License, or (at your option) any later version.
+#  
+#  SpaceLab-Decoder is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+#  GNU General Public License for more details.
+#  
+#  You should have received a copy of the GNU General Public
+#  License along with SpaceLab-Decoder; if not, see <http://www.gnu.org/licenses/>.
+#  
+#
+
+
+import numpy as np
+
+_DEFAULT_SAMPLE_RATE_HZ     = 48000
+_DEFAULT_BAUDRATE_BPS       = 1200
+
+class TimeSync:
+
+    def __init__(self):
+        pass
+
+    def get_bitstream(self, data, samp_rate=_DEFAULT_SAMPLE_RATE_HZ, baudrate=_DEFAULT_BAUDRATE_BPS):
+        sps = samp_rate/baudrate
+
+        samples = np.array(data, dtype=np.float64)
+
+        mu = 0.001  # Initial estimate of phase of sample
+        out = np.zeros(len(samples) + 10, dtype=np.complex64)
+
+        out_rail = np.zeros(len(samples) + 10, dtype=np.complex64) # Stores values, each iteration we need the previous 2 values plus current value
+
+        i_in = 0    # Input samples index
+        i_out = 2   # Output index (let first two outputs be 0)
+
+        while i_out < len(samples) and i_in+1 < len(samples):
+            out[i_out] = samples[i_in + int(mu)] # grab what we think is the "best" sample
+            out_rail[i_out] = int(np.real(out[i_out]) > 0) + 1j*int(np.imag(out[i_out]) > 0)
+
+            x = (out_rail[i_out] - out_rail[i_out-2]) * np.conj(out[i_out-1])
+            y = (out[i_out] - out[i_out-2]) * np.conj(out_rail[i_out-1])
+
+            mm_val = np.real(y - x)
+            mu += sps + 0.001*mm_val
+
+            i_in += int(np.floor(mu))   # Round down to nearest int since we are using it as an index
+            mu = mu - np.floor(mu)      # Remove the integer part of mu
+            i_out += 1                  # Increment output index
+
+        out = out[2:i_out]              # Remove the first two, and anything after i_out (that was never filled out)
+
+        bits = list()
+        for i in range(len(out)):
+            if out[i].real > 0:
+                bits.append(1)
+            else:
+                bits.append(0)
+
+        return bits