def detect(self, dsamples, receiver, offset):
# start looking at dsamples[offset] for the preamble sequence
sample_seq = receiver.mapper.bits2samples(self.barker())
local_carrier_result = sendrecv.local_carrier(receiver.fc, len(sample_seq), receiver.samplerate)
waveform = numpy.multiply(sample_seq, local_carrier_result)
demodulated_waveform = receiver.demodulate(waveform)
search_length = self.barkerlen()*3*receiver.mapper.spb
index = self.correlate(dsamples, demodulated_waveform[offset:(offset+search_length)])
return offset + index
def detect(self, dsamples, receiver, offset):
# start looking at dsamples[offset] for the preamble sequence
sample_seq = receiver.mapper.bits2samples(self.barker())
local_carrier_result = sendrecv.local_carrier(receiver.fc,
len(sample_seq),
receiver.samplerate)
waveform = numpy.multiply(sample_seq, local_carrier_result)
demodulated_waveform = receiver.demodulate(waveform)
search_length = self.barkerlen() * 3 * receiver.mapper.spb
index = self.correlate(
dsamples, demodulated_waveform[offset:(offset + search_length)])
return offset + index
def quadrature(samples, carrier_freq, config):
quadcarrier = sendrecv.local_carrier(carrier_freq, len(samples), config.samplerate, "demodquad")
return numpy.multiply(samples, quadcarrier)
def heterodyne(samples, carrier_freq, config):
sample_rate = config.samplerate
local_carrier = sendrecv.local_carrier(carrier_freq, len(samples), sample_rate)
return numpy.multiply(samples, local_carrier)