def detect(self, demodulated_samples, receiver, offset_hint, zero, one):
"""
Detects the preamble in an array of demodulated samples.
Arguments:
demodulated_samples = numpy.array of demodulated samples
receiver = Receiver associated with the reception of the
demodulated samples. Used to access the samples per bit,
sample rate, and carrier frequency of this data.
offset_hint = our best guess as to where the first 1 bit in
the samples begins
zero = best guess for V_0 for these samples
one = best guess for V_1 for these samples
Returns:
The index (as an int) into demodulated_samples where the
preamble is most likely to start.
"""
preamble_samples = util.bits_to_samples(self.data, receiver.spb, zero, one)
mod_presamples = util.modulate(receiver.fc, preamble_samples, receiver.sample_rate)
ideal_samples = receiver.demodulate_and_filter(mod_presamples)
if receiver.demod_type == Receiver.QUADRATURE:
ideal_samples = numpy.abs(ideal_samples)
samples_to_search = demodulated_samples[offset_hint:offset_hint + 3 * self.preamble_data_len() * receiver.spb]
pre_offset = self.correlate(ideal_samples, samples_to_search)
return offset_hint + pre_offset
def detect(self, demodulated_samples, receiver, offset_hint, zero, one):
'''
Detects the preamble in an array of demodulated samples.
Arguments:
demodulated_samples = numpy.array of demodulated samples
receiver = Receiver associated with the reception of the
demodulated samples. Used to access the samples per bit,
sample rate, and carrier frequency of this data.
offset_hint = our best guess as to where the first 1 bit in
the samples begins
zero = best guess for V_0 for these samples
one = best guess for V_1 for these samples
Returns:
The index (as an int) into demodulated_samples where the
preamble is most likely to start.
'''
#Get ideal set of preamble samples
#i.e. convert the preamble bits in self.data to samples, then modulate them
#then demodulate and filter them.
preamble_samples = util.bits_to_samples(self.data, receiver.spb, zero, one)
modulated_preambles = util.modulate(receiver.fc, preamble_samples, receiver.sample_rate)
demod_filter_preambles = receiver.demodulate_and_filter(modulated_preambles)
#correlate ideal preamble samples to the demodulated samples sequence
#and return the preamble start index
start_indx = offset_hint + self.correlate(demod_filter_preambles, demodulated_samples[offset_hint:])
return start_indx
def detect(self, demodulated_samples, receiver, offset_hint, zero, one):
'''
Detects the preamble in an array of demodulated samples.
Arguments:
demodulated_samples = numpy.array of demodulated samples
receiver = Receiver associated with the reception of the
demodulated samples. Used to access the samples per bit,
sample rate, and carrier frequency of this data.
offset_hint = our best guess as to where the first 1 bit in
the samples begins
zero = best guess for V_0 for these samples
one = best guess for V_1 for these samples
Returns:
The index (as an int) into demodulated_samples where the
preamble is most likely to start.
'''
samples=util.bits_to_samples(self.data,receiver.spb,zero,one)
modulated=util.modulate(receiver.fc, samples, receiver.sample_rate)
dmf_samples=receiver.demodulate_and_filter(modulated)
return offset_hint+self.max_correlation_index(dmf_samples,demodulated_samples[offset_hint:])
def detect(self, demodulated_samples, receiver, offset_hint, zero, one):
'''
Detects the preamble in an array of demodulated samples.
Arguments:
demodulated_samples = numpy.array of demodulated samples
receiver = Receiver associated with the reception of the
demodulated samples. Used to access the samples per bit,
sample rate, and carrier frequency of this data.
offset_hint = our best guess as to where the first 1 bit in
the samples begins
zero = best guess for V_0 for these samples
one = best guess for V_1 for these samples
Returns:
The index (as an int) into demodulated_samples where the
preamble is most likely to start.
'''
preamble_samples = util.bits_to_samples(self.data, receiver.spb, zero,
one)
modulated_samples = util.modulate(receiver.fc, preamble_samples,
receiver.sample_rate)
digitized_data = receiver.demodulate_and_filter(modulated_samples)
return offset_hint + self.correlate(digitized_data,
demodulated_samples[offset_hint:])
def heterodyne_demodulator(samples, sample_rate, carrier_freq):
return util.modulate(carrier_freq, samples, sample_rate)
def modulated_samples(self):
"""Returns the modulated signal (preamble + payload)."""
samples = self.sample_bits()
return util.modulate(self.fc, samples, self.sample_rate)
def modulated_samples(self):
'''Returns the modulated signal'''
samples = self.gain_samples()
return util.modulate(self.fc, samples, self.sample_rate)
def modulated_samples(self):
'''Returns the modulated signal (preamble + payload).'''
samples = self.sample_bits()
return util.modulate(self.fc, samples, self.sample_rate)
def heterodyne_demodulator(samples, sample_rate, carrier_freq):
'''Return the samples demodulated via heterodyne demodulation, using a
cosine of the given frequency (carrier_freq is specified in
hertz). You may need to convert between continuous-time and
discrete-time frequencies.'''
return util.modulate(carrier_freq,samples,sample_rate)
