def _update_filtered(self, translated): if translated is not None and self._taps is not None: filtered = TimeData(numpy.complex64(scipy.signal.lfilter(self._taps, 1, translated.samples)), translated.sampling_rate) filtered_abs = filtered.abs data_source = filtered_abs.samples numpy_source = NumpySource(data_source) peak_detector = blocks.peak_detector_fb(1.0, 0.3, 10, 0.001) sample_and_hold = blocks.sample_and_hold_ff() multiply_const = blocks.multiply_const_vff((0.5, )) subtract = blocks.sub_ff(1) numpy_sink = NumpySink(numpy.float32) top = gr.top_block() top.connect((numpy_source, 0), (peak_detector, 0)) top.connect((numpy_source, 0), (sample_and_hold, 0)) top.connect((numpy_source, 0), (subtract, 0)) top.connect((peak_detector, 0), (sample_and_hold, 1)) top.connect((sample_and_hold, 0), (multiply_const, 0)) top.connect((multiply_const, 0), (subtract, 1)) top.connect((subtract, 0), (numpy_sink, 0)) top.run() filtered = TimeData(numpy_sink.data, translated.sampling_rate) self.filtered_view.data = filtered # abs_min = filtered.abs.min # abs_max = filtered.abs.max # abs_mid = (abs_min + abs_max) / 2.0 # self.burst.filtered = filtered.abs - abs_mid self.burst.filtered = filtered else: self.filtered_view.data = None self.burst.filtered = None
def __init__(self, ts=(0+0j,), factor=0, alpha=0.01):
gr.hier_block2.__init__(
self, "timing_estimator_hier",
gr.io_signature(1, 1, gr.sizeof_gr_complex*1),
gr.io_signature(1, 1, gr.sizeof_char*1),
)
##################################################
# Parameters
##################################################
self.ts = ts
self.factor = factor
self.alpha = alpha
##################################################
# Blocks
##################################################
self.interp_fir_filter_xxx_0 = filter.interp_fir_filter_ccc(1, (numpy.conjugate(ts[::-1])))
self.blocks_peak_detector_xb_0_0 = blocks.peak_detector_fb(factor, factor, 0, alpha)
self.blocks_complex_to_mag_squared_0 = blocks.complex_to_mag_squared(1)
##################################################
# Connections
##################################################
self.connect((self.blocks_complex_to_mag_squared_0, 0), (self.blocks_peak_detector_xb_0_0, 0))
self.connect((self.interp_fir_filter_xxx_0, 0), (self.blocks_complex_to_mag_squared_0, 0))
self.connect((self.blocks_peak_detector_xb_0_0, 0), (self, 0))
self.connect((self, 0), (self.interp_fir_filter_xxx_0, 0))
def _update_filtered(self, translated): if translated is not None and self._taps is not None: filtered = TimeData(numpy.complex64(scipy.signal.lfilter(self._taps, 1, translated.samples)), translated.sampling_rate) filtered_abs = filtered.abs data_source = filtered_abs.samples numpy_source = NumpySource(data_source) peak_detector = blocks.peak_detector_fb(1.0, 0.3, 10, 0.001) sample_and_hold = blocks.sample_and_hold_ff() multiply_const = blocks.multiply_const_vff((0.5, )) subtract = blocks.sub_ff(1) numpy_sink = NumpySink(numpy.float32) top = gr.top_block() top.connect((numpy_source, 0), (peak_detector, 0)) top.connect((numpy_source, 0), (sample_and_hold, 0)) top.connect((numpy_source, 0), (subtract, 0)) top.connect((peak_detector, 0), (sample_and_hold, 1)) top.connect((sample_and_hold, 0), (multiply_const, 0)) top.connect((multiply_const, 0), (subtract, 1)) top.connect((subtract, 0), (numpy_sink, 0)) top.run() filtered = TimeData(numpy_sink.data, translated.sampling_rate) self.filtered_view.data = filtered # abs_min = filtered.abs.min # abs_max = filtered.abs.max # abs_mid = (abs_min + abs_max) / 2.0 # self.burst.filtered = filtered.abs - abs_mid self.burst.filtered = filtered else: self.filtered_view.data = None self.burst.filtered = None
def __init__(self, length, debug=False): """ Hierarchical block to detect Null symbols @param length length of the Null symbol (in samples) @param debug whether to write signals out to files """ gr.hier_block2.__init__(self,"detect_null", gr.io_signature(1, 1, gr.sizeof_gr_complex), # input signature gr.io_signature(1, 1, gr.sizeof_char)) # output signature # get the magnitude squared self.ns_c2magsquared = blocks.complex_to_mag_squared() # this wastes cpu cycles: # ns_detect_taps = [1]*length # self.ns_moving_sum = gr.fir_filter_fff(1,ns_detect_taps) # this isn't better: #self.ns_filter = gr.iir_filter_ffd([1]+[0]*(length-1)+[-1],[0,1]) # this does the same again, but is actually faster (outsourced to an independent block ..): self.ns_moving_sum = dab_swig.moving_sum_ff(length) self.ns_invert = blocks.multiply_const_ff(-1) # peak detector on the inverted, summed up signal -> we get the nulls (i.e. the position of the start of a frame) self.ns_peak_detect = blocks.peak_detector_fb(0.6,0.7,10,0.0001) # mostly found by try and error -> remember that the values are negative! # connect it all self.connect(self, self.ns_c2magsquared, self.ns_moving_sum, self.ns_invert, self.ns_peak_detect, self) if debug: self.connect(self.ns_invert, blocks.file_sink(gr.sizeof_float, "debug/ofdm_sync_dab_ns_filter_inv_f.dat")) self.connect(self.ns_peak_detect,blocks.file_sink(gr.sizeof_char, "debug/ofdm_sync_dab_peak_detect_b.dat"))
def __init__(self, ts, factor, alpha, samp_rate, freqs):
gr.hier_block2.__init__(
self, "freq_timing_estimator_hier",
gr.io_signature(1, 1, gr.sizeof_gr_complex*1),
gr.io_signaturev(3, 3, [gr.sizeof_char*1, gr.sizeof_float*1, gr.sizeof_float*1]),
)
##################################################
# Parameters
##################################################
self.ts = ts
self.factor = factor
self.alpha = alpha
self.samp_rate = samp_rate
self.freqs = freqs
self.n = n = len(freqs)
##################################################
# Blocks
##################################################
self._filter=[0]*self.n
self._c2mag2=[0]*self.n
for i in range(self.n):
self._filter[i]= filter.freq_xlating_fir_filter_ccc(1, (numpy.conjugate(self.ts[::-1])), self.freqs[i], self.samp_rate)
self._c2mag2[i] = blocks.complex_to_mag_squared(1)
self.blocks_max = blocks.max_ff(1)
self.blocks_peak_detector = blocks.peak_detector_fb(self.factor, self.factor, 0, self.alpha)
self.blocks_argmax = blocks.argmax_fs(1)
self.blocks_null_sink = blocks.null_sink(gr.sizeof_short*1)
self.digital_chunks_to_symbols = digital.chunks_to_symbols_sf((freqs), 1)
self.blocks_sample_and_hold = blocks.sample_and_hold_ff()
##################################################
# Connections
##################################################
for i in range(self.n):
self.connect((self, 0), (self._filter[i], 0))
self.connect((self._filter[i], 0), (self._c2mag2[i], 0))
self.connect((self._c2mag2[i], 0), (self.blocks_max, i))
self.connect((self._c2mag2[i], 0), (self.blocks_argmax, i))
self.connect((self.blocks_max, 0), (self.blocks_peak_detector, 0))
self.connect((self.blocks_peak_detector, 0), (self, 0))
self.connect((self.blocks_argmax, 0), (self.blocks_null_sink, 0))
self.connect((self.blocks_argmax, 1), (self.digital_chunks_to_symbols, 0))
self.connect((self.digital_chunks_to_symbols, 0), (self.blocks_sample_and_hold, 0))
self.connect((self.blocks_peak_detector, 0), (self.blocks_sample_and_hold, 1))
self.connect((self.blocks_sample_and_hold, 0), (self, 1))
self.connect((self.blocks_max, 0), (self, 2))
def __init__(self, length, debug=False):
"""
Hierarchical block to detect Null symbols
@param length length of the Null symbol (in samples)
@param debug whether to write signals out to files
"""
gr.hier_block2.__init__(
self,
"detect_null",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # input signature
gr.io_signature(1, 1, gr.sizeof_char)) # output signature
# get the magnitude squared
self.ns_c2magsquared = blocks.complex_to_mag_squared()
# this wastes cpu cycles:
# ns_detect_taps = [1]*length
# self.ns_moving_sum = gr.fir_filter_fff(1,ns_detect_taps)
# this isn't better:
#self.ns_filter = gr.iir_filter_ffd([1]+[0]*(length-1)+[-1],[0,1])
# this does the same again, but is actually faster (outsourced to an independent block ..):
self.ns_moving_sum = dab.moving_sum_ff(length)
self.ns_invert = blocks.multiply_const_ff(-1)
# peak detector on the inverted, summed up signal -> we get the nulls (i.e. the position of the start of a frame)
self.ns_peak_detect = blocks.peak_detector_fb(
0.6, 0.7, 10, 0.0001
) # mostly found by try and error -> remember that the values are negative!
# connect it all
self.connect(self, self.ns_c2magsquared, self.ns_moving_sum,
self.ns_invert, self.ns_peak_detect, self)
if debug:
self.connect(
self.ns_invert,
blocks.file_sink(gr.sizeof_float,
"debug/ofdm_sync_dab_ns_filter_inv_f.dat"))
self.connect(
self.ns_peak_detect,
blocks.file_sink(gr.sizeof_char,
"debug/ofdm_sync_dab_peak_detect_b.dat"))
def test_01(self):
tb = self.tb
data = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
expected_result = (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0)
src = blocks.vector_source_f(data, False)
regen = blocks.peak_detector_fb()
dst = blocks.vector_sink_b()
tb.connect(src, regen)
tb.connect(regen, dst)
tb.run()
dst_data = dst.data()
self.assertEqual(expected_result, dst_data)
def test_01(self):
tb = self.tb
data = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
expected_result = (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
src = blocks.vector_source_f(data, False)
regen = blocks.peak_detector_fb()
dst = blocks.vector_sink_b()
tb.connect(src, regen)
tb.connect(regen, dst)
tb.run()
dst_data = dst.data()
self.assertEqual(expected_result, dst_data)
def __init__(self, fft_length, cp_length, logging=False):
"""
OFDM synchronization using PN Correlation:
T. M. Schmidl and D. C. Cox, "Robust Frequency and Timing
Synchronization for OFDM," IEEE Trans. Communications, vol. 45,
no. 12, 1997.
"""
gr.hier_block2.__init__(self, "ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = blocks.add_const_cc(0)
# PN Sync
# Create a delay line
self.delay = blocks.delay(gr.sizeof_gr_complex, fft_length/2)
# Correlation from ML Sync
self.conjg = blocks.conjugate_cc();
self.corr = blocks.multiply_cc();
# Create a moving sum filter for the corr output
self.moving_sum_filter = filter.fir_filter_ccf(1, [1.0] * (fft_length//2))
# Create a moving sum filter for the input
self.inputmag2 = blocks.complex_to_mag_squared()
self.inputmovingsum = filter.fir_filter_fff(1, [1.0] * (fft_length//2))
self.square = blocks.multiply_ff()
self.normalize = blocks.divide_ff()
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = blocks.complex_to_mag_squared()
self.angle = blocks.complex_to_arg()
self.sample_and_hold = blocks.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.sub1 = blocks.add_const_ff(-1)
self.pk_detect = blocks.peak_detector_fb(0.20, 0.20, 30, 0.001)
self.connect(self, self.input)
# Calculate the frequency offset from the correlation of the preamble
self.connect(self.input, self.delay)
self.connect(self.input, (self.corr,0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr,1))
self.connect(self.corr, self.moving_sum_filter)
self.connect(self.moving_sum_filter, self.c2mag)
self.connect(self.moving_sum_filter, self.angle)
self.connect(self.angle, (self.sample_and_hold,0))
# Get the power of the input signal to normalize the output of the correlation
self.connect(self.input, self.inputmag2, self.inputmovingsum)
self.connect(self.inputmovingsum, (self.square,0))
self.connect(self.inputmovingsum, (self.square,1))
self.connect(self.square, (self.normalize,1))
self.connect(self.c2mag, (self.normalize,0))
# Create a moving sum filter for the corr output
matched_filter_taps = [1.0/cp_length for i in range(cp_length)]
self.matched_filter = filter.fir_filter_fff(1,matched_filter_taps)
self.connect(self.normalize, self.matched_filter)
self.connect(self.matched_filter, self.sub1, self.pk_detect)
#self.connect(self.matched_filter, self.pk_detect)
self.connect(self.pk_detect, (self.sample_and_hold,1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
self.connect(self.pk_detect, (self,1))
if logging:
self.connect(self.matched_filter, blocks.file_sink(gr.sizeof_float, "ofdm_sync_pn-mf_f.dat"))
self.connect(self.normalize, blocks.file_sink(gr.sizeof_float, "ofdm_sync_pn-theta_f.dat"))
self.connect(self.angle, blocks.file_sink(gr.sizeof_float, "ofdm_sync_pn-epsilon_f.dat"))
self.connect(self.pk_detect, blocks.file_sink(gr.sizeof_char, "ofdm_sync_pn-peaks_b.dat"))
self.connect(self.sample_and_hold, blocks.file_sink(gr.sizeof_float, "ofdm_sync_pn-sample_and_hold_f.dat"))
self.connect(self.input, blocks.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pn-input_c.dat"))
def __init__(self, fft_length, cp_length, snr, kstime, logging):
''' Maximum Likelihood OFDM synchronizer:
J. van de Beek, M. Sandell, and P. O. Borjesson, "ML Estimation
of Time and Frequency Offset in OFDM Systems," IEEE Trans.
Signal Processing, vol. 45, no. 7, pp. 1800-1805, 1997.
'''
gr.hier_block2.__init__(
self,
"ofdm_sync_ml",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float,
gr.sizeof_char)) # Output signature
self.input = blocks.add_const_cc(0)
SNR = 10.0**(snr / 10.0)
rho = SNR / (SNR + 1.0)
symbol_length = fft_length + cp_length
# ML Sync
# Energy Detection from ML Sync
self.connect(self, self.input)
# Create a delay line
self.delay = blocks.delay(gr.sizeof_gr_complex, fft_length)
self.connect(self.input, self.delay)
# magnitude squared blocks
self.magsqrd1 = blocks.complex_to_mag_squared()
self.magsqrd2 = blocks.complex_to_mag_squared()
self.adder = blocks.add_ff()
moving_sum_taps = [rho / 2 for i in range(cp_length)]
self.moving_sum_filter = filter.fir_filter_fff(1, moving_sum_taps)
self.connect(self.input, self.magsqrd1)
self.connect(self.delay, self.magsqrd2)
self.connect(self.magsqrd1, (self.adder, 0))
self.connect(self.magsqrd2, (self.adder, 1))
self.connect(self.adder, self.moving_sum_filter)
# Correlation from ML Sync
self.conjg = blocks.conjugate_cc()
self.mixer = blocks.multiply_cc()
movingsum2_taps = [1.0 for i in range(cp_length)]
self.movingsum2 = filter.fir_filter_ccf(1, movingsum2_taps)
# Correlator data handler
self.c2mag = blocks.complex_to_mag()
self.angle = blocks.complex_to_arg()
self.connect(self.input, (self.mixer, 1))
self.connect(self.delay, self.conjg, (self.mixer, 0))
self.connect(self.mixer, self.movingsum2, self.c2mag)
self.connect(self.movingsum2, self.angle)
# ML Sync output arg, need to find maximum point of this
self.diff = blocks.sub_ff()
self.connect(self.c2mag, (self.diff, 0))
self.connect(self.moving_sum_filter, (self.diff, 1))
#ML measurements input to sampler block and detect
self.f2c = blocks.float_to_complex()
self.pk_detect = blocks.peak_detector_fb(0.2, 0.25, 30, 0.0005)
self.sample_and_hold = blocks.sample_and_hold_ff()
# use the sync loop values to set the sampler and the NCO
# self.diff = theta
# self.angle = epsilon
self.connect(self.diff, self.pk_detect)
# The DPLL corrects for timing differences between CP correlations
use_dpll = 0
if use_dpll:
self.dpll = gr.dpll_bb(float(symbol_length), 0.01)
self.connect(self.pk_detect, self.dpll)
self.connect(self.dpll, (self.sample_and_hold, 1))
else:
self.connect(self.pk_detect, (self.sample_and_hold, 1))
self.connect(self.angle, (self.sample_and_hold, 0))
################################
# correlate against known symbol
# This gives us the same timing signal as the PN sync block only on the preamble
# we don't use the signal generated from the CP correlation because we don't want
# to readjust the timing in the middle of the packet or we ruin the equalizer settings.
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.kscorr = filter.fir_filter_ccc(1, kstime)
self.corrmag = blocks.complex_to_mag_squared()
self.div = blocks.divide_ff()
# The output signature of the correlation has a few spikes because the rest of the
# system uses the repeated preamble symbol. It needs to work that generically if
# anyone wants to use this against a WiMAX-like signal since it, too, repeats.
# The output theta of the correlator above is multiplied with this correlation to
# identify the proper peak and remove other products in this cross-correlation
self.threshold_factor = 0.1
self.slice = blocks.threshold_ff(self.threshold_factor,
self.threshold_factor, 0)
self.f2b = blocks.float_to_char()
self.b2f = blocks.char_to_float()
self.mul = blocks.multiply_ff()
# Normalize the power of the corr output by the energy. This is not really needed
# and could be removed for performance, but it makes for a cleaner signal.
# if this is removed, the threshold value needs adjustment.
self.connect(self.input, self.kscorr, self.corrmag, (self.div, 0))
self.connect(self.moving_sum_filter, (self.div, 1))
self.connect(self.div, (self.mul, 0))
self.connect(self.pk_detect, self.b2f, (self.mul, 1))
self.connect(self.mul, self.slice)
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self, 0))
self.connect(self.slice, self.f2b, (self, 1))
if logging:
self.connect(
self.moving_sum_filter,
blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-energy_f.dat"))
self.connect(
self.diff,
blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-theta_f.dat"))
self.connect(
self.angle,
blocks.file_sink(gr.sizeof_float,
"ofdm_sync_ml-epsilon_f.dat"))
self.connect(
self.corrmag,
blocks.file_sink(gr.sizeof_float,
"ofdm_sync_ml-corrmag_f.dat"))
self.connect(
self.kscorr,
blocks.file_sink(gr.sizeof_gr_complex,
"ofdm_sync_ml-kscorr_c.dat"))
self.connect(
self.div,
blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-div_f.dat"))
self.connect(
self.mul,
blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-mul_f.dat"))
self.connect(
self.slice,
blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-slice_f.dat"))
self.connect(
self.pk_detect,
blocks.file_sink(gr.sizeof_char, "ofdm_sync_ml-peaks_b.dat"))
if use_dpll:
self.connect(
self.dpll,
blocks.file_sink(gr.sizeof_char,
"ofdm_sync_ml-dpll_b.dat"))
self.connect(
self.sample_and_hold,
blocks.file_sink(gr.sizeof_float,
"ofdm_sync_ml-sample_and_hold_f.dat"))
self.connect(
self.input,
blocks.file_sink(gr.sizeof_gr_complex,
"ofdm_sync_ml-input_c.dat"))
def __init__(self, fft_length, cp_length, kstime, overrate, logging=True):
"""
OFDM synchronization using PN Correlation:
T. M. Schmidl and D. C. Cox, "Robust Frequency and Timing
Synchonization for OFDM," IEEE Trans. Communications, vol. 45,
no. 12, 1997.
"""
gr.hier_block2.__init__(
self,
"ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float,
gr.sizeof_char)) # Output signature
self.input = blocks.add_const_cc(0)
# cross-correlate with the known symbol
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.crosscorr_filter = filter.fir_filter_ccc(1, kstime)
# PN Sync
self.corrmag = blocks.complex_to_mag_squared()
self.delay = blocks.delay(gr.sizeof_gr_complex,
fft_length * overrate / 2)
# Correlation from ML Sync
self.conjg = blocks.conjugate_cc()
self.corr = blocks.multiply_cc()
#self.sub = blocks.add_const_ff(-1)
self.pk_detect = blocks.peak_detector_fb(0.40, 0.25,
fft_length * overrate,
0.00000000000)
self.connect(self, self.input)
self.connect(self.input, self.crosscorr_filter)
self.connect(self.crosscorr_filter, self.corrmag)
#self.inputmag = blocks.complex_to_mag_squared()
#self.normalize = blocks.divide_ff()
#self.inputmovingsum = filter.fir_filter_fff(1, [1.0] * (fft_length//2))
self.square = blocks.multiply_ff()
#self.connect(self.input,self.inputmag,self.inputmovingsum)
self.connect(self.corrmag, (self.square, 0))
self.connect(self.corrmag, (self.square, 1))
self.dsquare = blocks.multiply_ff()
self.connect(self.square, (self.dsquare, 0))
self.connect(self.square, (self.dsquare, 1))
self.connect(self.dsquare, self.pk_detect)
# Create a moving sum filter for the corr output
self.moving_sum_filter = filter.fir_filter_ccf(
1, [1.0] * (fft_length * overrate // 2))
# Get magnitude (peaks) and angle (phase/freq error)
self.angle = blocks.complex_to_arg()
self.sample_and_hold = blocks.sample_and_hold_ff()
# Calculate the frequency offset from the correlation of the preamble
self.connect(self.input, self.delay)
self.connect(self.input, (self.corr, 0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr, 1))
self.connect(self.corr, self.moving_sum_filter)
self.connect(self.moving_sum_filter, self.angle)
self.connect(self.angle, (self.sample_and_hold, 0))
self.connect(self.pk_detect, (self.sample_and_hold, 1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self, 0))
self.connect(self.pk_detect, (self, 1))
if logging:
self.connect(
self.dsquare,
blocks.file_sink(gr.sizeof_float, "ofdm_sync_pn-dsquare.dat"))
self.connect(
self.corrmag,
blocks.file_sink(gr.sizeof_float, "ofdm_sync_pn-corrmag.dat"))
self.connect(
self.angle,
blocks.file_sink(gr.sizeof_float,
"ofdm_sync_pn-epsilon_f.dat"))
self.connect(
self.pk_detect,
blocks.file_sink(gr.sizeof_char, "ofdm_sync_pn-peaks_b.dat"))
self.connect(
self.sample_and_hold,
blocks.file_sink(gr.sizeof_float,
"ofdm_sync_pn-sample_and_hold_f.dat"))
self.connect(
self.input,
blocks.file_sink(gr.sizeof_gr_complex,
"ofdm_sync_pn-input_c.dat"))
def __init__(self, seq1, seq2, factor, alpha, freqs):
"""
Description:
frequency timing estimator class does frequency/timing acquisition from scratch.It uses a bank of parallel correlators at each specified frequency. It then takes the max abs value of all these and passes it through a peak detector to find timing.
Args:
seq1: sequence1 of kronecker filter, which is the given training sequence.
seq2: sequence2 of kronecker filter, which is the pulse for each training symbol.
factor: the rise and fall factors in peak detector, which is the factor determining when a peak has started and ended. In the peak detector, an average of the signal is calculated. When the value of the signal goes over factor*average, we start looking for a peak. When the value of the signal goes below factor*average, we stop looking for a peak.
alpha: the smoothing factor of a moving average filter used in the peak detector taking values in (0,1).
freqs: the vector of normalized center frequencies for each matched filter. Note that for a training sequence of length Nt, each matched filter can recover a sequence with normalized frequency offset ~ 1/(2Nt).
"""
gr.hier_block2.__init__(self,
"freq_timing_estimator",
gr.io_signature(1, 1, gr.sizeof_gr_complex*1),
gr.io_signaturev(3, 3, [gr.sizeof_char*1, gr.sizeof_float*1, gr.sizeof_float*1]),
)
##################################################
# Parameters
##################################################
self.seq1 = seq1
self.seq2 = seq2
self.factor = factor
self.alpha = alpha
self.freqs = freqs
self.n = n = len(freqs)
##################################################
# Blocks
##################################################
self._filter=[0]*self.n
self._c2mag2=[0]*self.n
for i in range(self.n):
self._filter[i]= cdma.kronecker_filter(seq1,seq2,1,self.freqs[i])
#self._filter[i]= filter.freq_xlating_fir_filter_ccc(1, numpy.kron(seq1,seq2), self.freqs[i], 1)
self._c2mag2[i] = blocks.complex_to_mag_squared(1)
self.blocks_max = blocks.max_ff(1)
self.blocks_peak_detector = blocks.peak_detector_fb(self.factor, self.factor, 0, self.alpha)
self.blocks_argmax = blocks.argmax_fs(1)
self.blocks_null_sink = blocks.null_sink(gr.sizeof_short*1)
self.digital_chunks_to_symbols = digital.chunks_to_symbols_sf((freqs), 1)
self.blocks_sample_and_hold = blocks.sample_and_hold_ff()
##################################################
# Connections
##################################################
for i in range(self.n):
self.connect((self, 0), (self._filter[i], 0))
self.connect((self._filter[i], 0), (self._c2mag2[i], 0))
self.connect((self._c2mag2[i], 0), (self.blocks_max, i))
self.connect((self._c2mag2[i], 0), (self.blocks_argmax, i))
self.connect((self.blocks_max, 0), (self.blocks_peak_detector, 0))
self.connect((self.blocks_peak_detector, 0), (self, 0))
self.connect((self.blocks_argmax, 0), (self.blocks_null_sink, 0))
self.connect((self.blocks_argmax, 1), (self.digital_chunks_to_symbols, 0))
self.connect((self.digital_chunks_to_symbols, 0), (self.blocks_sample_and_hold, 0))
self.connect((self.blocks_peak_detector, 0), (self.blocks_sample_and_hold, 1))
self.connect((self.blocks_sample_and_hold, 0), (self, 1))
self.connect((self.blocks_max, 0), (self, 2))
def __init__(self, fft_length, cp_length, logging=False):
"""
OFDM synchronization using PN Correlation:
T. M. Schmidl and D. C. Cox, "Robust Frequency and Timing
Synchronization for OFDM," IEEE Trans. Communications, vol. 45,
no. 12, 1997.
"""
gr.hier_block2.__init__(
self,
"ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float,
gr.sizeof_char)) # Output signature
self.input = blocks.add_const_cc(0)
# PN Sync
# Create a delay line
self.delay = blocks.delay(gr.sizeof_gr_complex, fft_length / 2)
# Correlation from ML Sync
self.conjg = blocks.conjugate_cc()
self.corr = blocks.multiply_cc()
# Create a moving sum filter for the corr output
self.moving_sum_filter = filter.fir_filter_ccf(1, [1.0] *
(fft_length // 2))
# Create a moving sum filter for the input
self.inputmag2 = blocks.complex_to_mag_squared()
self.inputmovingsum = filter.fir_filter_fff(1,
[1.0] * (fft_length // 2))
self.square = blocks.multiply_ff()
self.normalize = blocks.divide_ff()
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = blocks.complex_to_mag_squared()
self.angle = blocks.complex_to_arg()
self.sample_and_hold = blocks.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.sub1 = blocks.add_const_ff(-1)
self.pk_detect = blocks.peak_detector_fb(0.20, 0.20, 30, 0.001)
self.connect(self, self.input)
# Calculate the frequency offset from the correlation of the preamble
self.connect(self.input, self.delay)
self.connect(self.input, (self.corr, 0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr, 1))
self.connect(self.corr, self.moving_sum_filter)
self.connect(self.moving_sum_filter, self.c2mag)
self.connect(self.moving_sum_filter, self.angle)
self.connect(self.angle, (self.sample_and_hold, 0))
# Get the power of the input signal to normalize the output of the correlation
self.connect(self.input, self.inputmag2, self.inputmovingsum)
self.connect(self.inputmovingsum, (self.square, 0))
self.connect(self.inputmovingsum, (self.square, 1))
self.connect(self.square, (self.normalize, 1))
self.connect(self.c2mag, (self.normalize, 0))
# Create a moving sum filter for the corr output
matched_filter_taps = [1.0 / cp_length for i in range(cp_length)]
self.matched_filter = filter.fir_filter_fff(1, matched_filter_taps)
self.connect(self.normalize, self.matched_filter)
self.connect(self.matched_filter, self.sub1, self.pk_detect)
#self.connect(self.matched_filter, self.pk_detect)
self.connect(self.pk_detect, (self.sample_and_hold, 1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self, 0))
self.connect(self.pk_detect, (self, 1))
if logging:
self.connect(
self.matched_filter,
blocks.file_sink(gr.sizeof_float, "ofdm_sync_pn-mf_f.dat"))
self.connect(
self.normalize,
blocks.file_sink(gr.sizeof_float, "ofdm_sync_pn-theta_f.dat"))
self.connect(
self.angle,
blocks.file_sink(gr.sizeof_float,
"ofdm_sync_pn-epsilon_f.dat"))
self.connect(
self.pk_detect,
blocks.file_sink(gr.sizeof_char, "ofdm_sync_pn-peaks_b.dat"))
self.connect(
self.sample_and_hold,
blocks.file_sink(gr.sizeof_float,
"ofdm_sync_pn-sample_and_hold_f.dat"))
self.connect(
self.input,
blocks.file_sink(gr.sizeof_gr_complex,
"ofdm_sync_pn-input_c.dat"))
def __init__(self, ts, factor, alpha, samp_rate, freqs):
"""
Description:
This block is designed to perform frequency and timing acquisition for a known training sequence in the presense of frequency and timing offset and noise. Its input is a complex stream. It has three outputs:
1) a stream of flags (bytes) indicating the begining of the training sequence (to be used from subsequent blocks to "chop" the incoming stream,
2) a stream with the current acquired frequency offset, and
3) a stream with the current acquired peak of the matched filter
Internally, it consists of a user defined number of parallel matched filters (as many as the size of the freqs vector), each consistng of a frequency Xlating FIR filter with sample rate samp_rate, filter taps matched to the training sequence ts, and center frequency freqs[i]. The filter outputs are magnitude squared and passed through a max block and then through a peak detector.
Args:
ts: the training sequence. For example, in DSSS system, it's the chip-based spread training sequence.
factor: the rise and fall factors in peak detector, which is the factor determining when a peak has started and ended. In the peak detector, an average of the signal is calculated. When the value of the signal goes over factor*average, we start looking for a peak. When the value of the signal goes below factor*average, we stop looking for a peak. factor takes values in (0,1).
alpha: the smoothing factor of a moving average filter used in the peak detector takeng values in (0,1).
samp_rate: the sample rate of the system, which is used in the freq_xlating_fir_filter.
freqs: the vector of center frequencies for each matched filter. Note that for a training sequence of length Nt, each matched filter can recover a sequence with normalized frequency offset ~ 1/(2Nt).
"""
gr.hier_block2.__init__(
self, "freq_timing_estimator",
gr.io_signature(1, 1, gr.sizeof_gr_complex*1),
gr.io_signaturev(3, 3, [gr.sizeof_char*1, gr.sizeof_float*1, gr.sizeof_float*1]),
)
##################################################
# Parameters
##################################################
self.ts = ts
self.factor = factor
self.alpha = alpha
self.samp_rate = samp_rate
self.freqs = freqs
self.n = n = len(freqs)
##################################################
# Blocks
##################################################
self._filter=[0]*self.n
self._c2mag2=[0]*self.n
for i in range(self.n):
self._filter[i]= filter.freq_xlating_fir_filter_ccc(1, (numpy.conjugate(self.ts[::-1])), self.freqs[i], self.samp_rate)
self._c2mag2[i] = blocks.complex_to_mag_squared(1)
self.blocks_max = blocks.max_ff(1)
self.blocks_peak_detector = blocks.peak_detector_fb(self.factor, self.factor, 0, self.alpha)
self.blocks_argmax = blocks.argmax_fs(1)
self.blocks_null_sink = blocks.null_sink(gr.sizeof_short*1)
self.digital_chunks_to_symbols = digital.chunks_to_symbols_sf((freqs), 1)
self.blocks_sample_and_hold = blocks.sample_and_hold_ff()
##################################################
# Connections
##################################################
for i in range(self.n):
self.connect((self, 0), (self._filter[i], 0))
self.connect((self._filter[i], 0), (self._c2mag2[i], 0))
self.connect((self._c2mag2[i], 0), (self.blocks_max, i))
self.connect((self._c2mag2[i], 0), (self.blocks_argmax, i))
self.connect((self.blocks_max, 0), (self.blocks_peak_detector, 0))
self.connect((self.blocks_peak_detector, 0), (self, 0))
self.connect((self.blocks_argmax, 0), (self.blocks_null_sink, 0))
self.connect((self.blocks_argmax, 1), (self.digital_chunks_to_symbols, 0))
self.connect((self.digital_chunks_to_symbols, 0), (self.blocks_sample_and_hold, 0))
self.connect((self.blocks_peak_detector, 0), (self.blocks_sample_and_hold, 1))
self.connect((self.blocks_sample_and_hold, 0), (self, 1))
self.connect((self.blocks_max, 0), (self, 2))
def __init__(self, fft_length, cp_length, snr, kstime, logging):
''' Maximum Likelihood OFDM synchronizer:
J. van de Beek, M. Sandell, and P. O. Borjesson, "ML Estimation
of Time and Frequency Offset in OFDM Systems," IEEE Trans.
Signal Processing, vol. 45, no. 7, pp. 1800-1805, 1997.
'''
gr.hier_block2.__init__(self, "ofdm_sync_ml",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = blocks.add_const_cc(0)
SNR = 10.0**(snr / 10.0)
rho = SNR / (SNR + 1.0)
symbol_length = fft_length + cp_length
# ML Sync
# Energy Detection from ML Sync
self.connect(self, self.input)
# Create a delay line
self.delay = blocks.delay(gr.sizeof_gr_complex, fft_length)
self.connect(self.input, self.delay)
# magnitude squared blocks
self.magsqrd1 = blocks.complex_to_mag_squared()
self.magsqrd2 = blocks.complex_to_mag_squared()
self.adder = blocks.add_ff()
moving_sum_taps = [rho / 2 for i in range(cp_length)]
self.moving_sum_filter = filter.fir_filter_fff(1,moving_sum_taps)
self.connect(self.input,self.magsqrd1)
self.connect(self.delay,self.magsqrd2)
self.connect(self.magsqrd1,(self.adder,0))
self.connect(self.magsqrd2,(self.adder,1))
self.connect(self.adder,self.moving_sum_filter)
# Correlation from ML Sync
self.conjg = blocks.conjugate_cc();
self.mixer = blocks.multiply_cc();
movingsum2_taps = [1.0 for i in range(cp_length)]
self.movingsum2 = filter.fir_filter_ccf(1,movingsum2_taps)
# Correlator data handler
self.c2mag = blocks.complex_to_mag()
self.angle = blocks.complex_to_arg()
self.connect(self.input,(self.mixer,1))
self.connect(self.delay,self.conjg,(self.mixer,0))
self.connect(self.mixer,self.movingsum2,self.c2mag)
self.connect(self.movingsum2,self.angle)
# ML Sync output arg, need to find maximum point of this
self.diff = blocks.sub_ff()
self.connect(self.c2mag,(self.diff,0))
self.connect(self.moving_sum_filter,(self.diff,1))
#ML measurements input to sampler block and detect
self.f2c = blocks.float_to_complex()
self.pk_detect = blocks.peak_detector_fb(0.2, 0.25, 30, 0.0005)
self.sample_and_hold = blocks.sample_and_hold_ff()
# use the sync loop values to set the sampler and the NCO
# self.diff = theta
# self.angle = epsilon
self.connect(self.diff, self.pk_detect)
# The DPLL corrects for timing differences between CP correlations
use_dpll = 0
if use_dpll:
self.dpll = gr.dpll_bb(float(symbol_length),0.01)
self.connect(self.pk_detect, self.dpll)
self.connect(self.dpll, (self.sample_and_hold,1))
else:
self.connect(self.pk_detect, (self.sample_and_hold,1))
self.connect(self.angle, (self.sample_and_hold,0))
################################
# correlate against known symbol
# This gives us the same timing signal as the PN sync block only on the preamble
# we don't use the signal generated from the CP correlation because we don't want
# to readjust the timing in the middle of the packet or we ruin the equalizer settings.
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.kscorr = filter.fir_filter_ccc(1, kstime)
self.corrmag = blocks.complex_to_mag_squared()
self.div = blocks.divide_ff()
# The output signature of the correlation has a few spikes because the rest of the
# system uses the repeated preamble symbol. It needs to work that generically if
# anyone wants to use this against a WiMAX-like signal since it, too, repeats.
# The output theta of the correlator above is multiplied with this correlation to
# identify the proper peak and remove other products in this cross-correlation
self.threshold_factor = 0.1
self.slice = blocks.threshold_ff(self.threshold_factor, self.threshold_factor, 0)
self.f2b = blocks.float_to_char()
self.b2f = blocks.char_to_float()
self.mul = blocks.multiply_ff()
# Normalize the power of the corr output by the energy. This is not really needed
# and could be removed for performance, but it makes for a cleaner signal.
# if this is removed, the threshold value needs adjustment.
self.connect(self.input, self.kscorr, self.corrmag, (self.div,0))
self.connect(self.moving_sum_filter, (self.div,1))
self.connect(self.div, (self.mul,0))
self.connect(self.pk_detect, self.b2f, (self.mul,1))
self.connect(self.mul, self.slice)
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
self.connect(self.slice, self.f2b, (self,1))
if logging:
self.connect(self.moving_sum_filter, blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-energy_f.dat"))
self.connect(self.diff, blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-theta_f.dat"))
self.connect(self.angle, blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-epsilon_f.dat"))
self.connect(self.corrmag, blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-corrmag_f.dat"))
self.connect(self.kscorr, blocks.file_sink(gr.sizeof_gr_complex, "ofdm_sync_ml-kscorr_c.dat"))
self.connect(self.div, blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-div_f.dat"))
self.connect(self.mul, blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-mul_f.dat"))
self.connect(self.slice, blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-slice_f.dat"))
self.connect(self.pk_detect, blocks.file_sink(gr.sizeof_char, "ofdm_sync_ml-peaks_b.dat"))
if use_dpll:
self.connect(self.dpll, blocks.file_sink(gr.sizeof_char, "ofdm_sync_ml-dpll_b.dat"))
self.connect(self.sample_and_hold, blocks.file_sink(gr.sizeof_float, "ofdm_sync_ml-sample_and_hold_f.dat"))
self.connect(self.input, blocks.file_sink(gr.sizeof_gr_complex, "ofdm_sync_ml-input_c.dat"))
def __init__(self, seq1, seq2, factor, alpha, samp_rate, freqs):
"""
Description:
This block is functionally equivalent to the frequency_timing_estimator block, except from the fact that each filter is matched to a sequence that can be written as the kronecker product of seq1 and seq2.
Args:
seq1: sequence1 of kronecker filter, which is the given training sequence.
seq2: sequence2 of kronecker filter, which is the pulse for each training symbol.
factor: the rise and fall factors in peak detector, which is the factor determining when a peak has started and ended. In the peak detector, an average of the signal is calculated. When the value of the signal goes over factor*average, we start looking for a peak. When the value of the signal goes below factor*average, we stop looking for a peak. factor takes values in (0,1).
alpha: the smoothing factor of a moving average filter used in the peak detector takeng values in (0,1).
samp_rate: the sample rate of the system, which is used in the kronecker_filter.
freqs: the vector of center frequencies for each matched filter. Note that for a training sequence of length Nt, each matched filter can recover a sequence with normalized frequency offset ~ 1/(2Nt).
"""
gr.hier_block2.__init__(self,
"freq_timing_estimator",
gr.io_signature(1, 1, gr.sizeof_gr_complex*1),
gr.io_signaturev(3, 3, [gr.sizeof_char*1, gr.sizeof_float*1, gr.sizeof_float*1]),
)
##################################################
# Parameters
##################################################
self.seq1 = seq1
self.seq2 = seq2
self.factor = factor
self.alpha = alpha
self.samp_rate = samp_rate
self.freqs = freqs
self.n = n = len(freqs)
##################################################
# Blocks
##################################################
self._filter=[0]*self.n
self._c2mag2=[0]*self.n
for i in range(self.n):
self._filter[i]= cdma.kronecker_filter(seq1,seq2,samp_rate,self.freqs[i])
#self._filter[i]= filter.freq_xlating_fir_filter_ccc(1, (numpy.conjugate(self.ts[::-1])), self.freqs[i], self.samp_rate)
self._c2mag2[i] = blocks.complex_to_mag_squared(1)
self.blocks_max = blocks.max_ff(1)
self.blocks_peak_detector = blocks.peak_detector_fb(self.factor, self.factor, 0, self.alpha)
self.blocks_argmax = blocks.argmax_fs(1)
self.blocks_null_sink = blocks.null_sink(gr.sizeof_short*1)
self.digital_chunks_to_symbols = digital.chunks_to_symbols_sf((freqs), 1)
self.blocks_sample_and_hold = blocks.sample_and_hold_ff()
##################################################
# Connections
##################################################
for i in range(self.n):
self.connect((self, 0), (self._filter[i], 0))
self.connect((self._filter[i], 0), (self._c2mag2[i], 0))
self.connect((self._c2mag2[i], 0), (self.blocks_max, i))
self.connect((self._c2mag2[i], 0), (self.blocks_argmax, i))
self.connect((self.blocks_max, 0), (self.blocks_peak_detector, 0))
self.connect((self.blocks_peak_detector, 0), (self, 0))
self.connect((self.blocks_argmax, 0), (self.blocks_null_sink, 0))
self.connect((self.blocks_argmax, 1), (self.digital_chunks_to_symbols, 0))
self.connect((self.digital_chunks_to_symbols, 0), (self.blocks_sample_and_hold, 0))
self.connect((self.blocks_peak_detector, 0), (self.blocks_sample_and_hold, 1))
self.connect((self.blocks_sample_and_hold, 0), (self, 1))
self.connect((self.blocks_max, 0), (self, 2))
def __init__(self):
gr.top_block.__init__(self, "Not titled yet")
Qt.QWidget.__init__(self)
self.setWindowTitle("Not titled yet")
qtgui.util.check_set_qss()
try:
self.setWindowIcon(Qt.QIcon.fromTheme('gnuradio-grc'))
except:
pass
self.top_scroll_layout = Qt.QVBoxLayout()
self.setLayout(self.top_scroll_layout)
self.top_scroll = Qt.QScrollArea()
self.top_scroll.setFrameStyle(Qt.QFrame.NoFrame)
self.top_scroll_layout.addWidget(self.top_scroll)
self.top_scroll.setWidgetResizable(True)
self.top_widget = Qt.QWidget()
self.top_scroll.setWidget(self.top_widget)
self.top_layout = Qt.QVBoxLayout(self.top_widget)
self.top_grid_layout = Qt.QGridLayout()
self.top_layout.addLayout(self.top_grid_layout)
self.settings = Qt.QSettings("GNU Radio", "arduino")
try:
if StrictVersion(Qt.qVersion()) < StrictVersion("5.0.0"):
self.restoreGeometry(
self.settings.value("geometry").toByteArray())
else:
self.restoreGeometry(self.settings.value("geometry"))
except:
pass
##################################################
# Variables
##################################################
self.samp_rate = samp_rate = 2.048e6
self.decimation = decimation = 64
self.clock_freq = clock_freq = 1e3
self.center_freq = center_freq = 434e6
##################################################
# Blocks
##################################################
self.rtlsdr_source_0 = osmosdr.source(args="numchan=" + str(1) + " " +
"")
self.rtlsdr_source_0.set_time_unknown_pps(osmosdr.time_spec_t())
self.rtlsdr_source_0.set_sample_rate(samp_rate)
self.rtlsdr_source_0.set_center_freq(center_freq, 0)
self.rtlsdr_source_0.set_freq_corr(0, 0)
self.rtlsdr_source_0.set_gain(0, 0)
self.rtlsdr_source_0.set_if_gain(20, 0)
self.rtlsdr_source_0.set_bb_gain(20, 0)
self.rtlsdr_source_0.set_antenna('', 0)
self.rtlsdr_source_0.set_bandwidth(0, 0)
self.qtgui_time_sink_x_1_0 = qtgui.time_sink_f(
1024, #size
samp_rate / decimation, #samp_rate
'Digital', #name
2 #number of inputs
)
self.qtgui_time_sink_x_1_0.set_update_time(0.10)
self.qtgui_time_sink_x_1_0.set_y_axis(-1, 1)
self.qtgui_time_sink_x_1_0.set_y_label('Amplitude', "")
self.qtgui_time_sink_x_1_0.enable_tags(True)
self.qtgui_time_sink_x_1_0.set_trigger_mode(qtgui.TRIG_MODE_AUTO,
qtgui.TRIG_SLOPE_POS, 0.0,
-10e-3, 0, "")
self.qtgui_time_sink_x_1_0.enable_autoscale(False)
self.qtgui_time_sink_x_1_0.enable_grid(False)
self.qtgui_time_sink_x_1_0.enable_axis_labels(True)
self.qtgui_time_sink_x_1_0.enable_control_panel(False)
self.qtgui_time_sink_x_1_0.enable_stem_plot(False)
labels = [
'Signal 1', 'Signal 2', 'Signal 3', 'Signal 4', 'Signal 5',
'Signal 6', 'Signal 7', 'Signal 8', 'Signal 9', 'Signal 10'
]
widths = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
colors = [
'blue', 'red', 'green', 'black', 'cyan', 'magenta', 'yellow',
'dark red', 'dark green', 'dark blue'
]
alphas = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
styles = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
markers = [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
for i in range(2):
if len(labels[i]) == 0:
self.qtgui_time_sink_x_1_0.set_line_label(
i, "Data {0}".format(i))
else:
self.qtgui_time_sink_x_1_0.set_line_label(i, labels[i])
self.qtgui_time_sink_x_1_0.set_line_width(i, widths[i])
self.qtgui_time_sink_x_1_0.set_line_color(i, colors[i])
self.qtgui_time_sink_x_1_0.set_line_style(i, styles[i])
self.qtgui_time_sink_x_1_0.set_line_marker(i, markers[i])
self.qtgui_time_sink_x_1_0.set_line_alpha(i, alphas[i])
self._qtgui_time_sink_x_1_0_win = sip.wrapinstance(
self.qtgui_time_sink_x_1_0.pyqwidget(), Qt.QWidget)
self.top_grid_layout.addWidget(self._qtgui_time_sink_x_1_0_win)
self.qtgui_time_sink_x_0 = qtgui.time_sink_f(
1024, #size
samp_rate, #samp_rate
"", #name
1 #number of inputs
)
self.qtgui_time_sink_x_0.set_update_time(0.10)
self.qtgui_time_sink_x_0.set_y_axis(-1, 1)
self.qtgui_time_sink_x_0.set_y_label('Amplitude', "")
self.qtgui_time_sink_x_0.enable_tags(True)
self.qtgui_time_sink_x_0.set_trigger_mode(qtgui.TRIG_MODE_TAG,
qtgui.TRIG_SLOPE_POS, 0.0,
-1e-3, 0, 'burst')
self.qtgui_time_sink_x_0.enable_autoscale(False)
self.qtgui_time_sink_x_0.enable_grid(False)
self.qtgui_time_sink_x_0.enable_axis_labels(True)
self.qtgui_time_sink_x_0.enable_control_panel(False)
self.qtgui_time_sink_x_0.enable_stem_plot(False)
labels = [
'Signal 1', 'Signal 2', 'Signal 3', 'Signal 4', 'Signal 5',
'Signal 6', 'Signal 7', 'Signal 8', 'Signal 9', 'Signal 10'
]
widths = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
colors = [
'blue', 'red', 'green', 'black', 'cyan', 'magenta', 'yellow',
'dark red', 'dark green', 'dark blue'
]
alphas = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
styles = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
markers = [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
for i in range(1):
if len(labels[i]) == 0:
self.qtgui_time_sink_x_0.set_line_label(
i, "Data {0}".format(i))
else:
self.qtgui_time_sink_x_0.set_line_label(i, labels[i])
self.qtgui_time_sink_x_0.set_line_width(i, widths[i])
self.qtgui_time_sink_x_0.set_line_color(i, colors[i])
self.qtgui_time_sink_x_0.set_line_style(i, styles[i])
self.qtgui_time_sink_x_0.set_line_marker(i, markers[i])
self.qtgui_time_sink_x_0.set_line_alpha(i, alphas[i])
self._qtgui_time_sink_x_0_win = sip.wrapinstance(
self.qtgui_time_sink_x_0.pyqwidget(), Qt.QWidget)
self.top_grid_layout.addWidget(self._qtgui_time_sink_x_0_win)
self.qtgui_freq_sink_x_2 = qtgui.freq_sink_c(
1024, #size
firdes.WIN_BLACKMAN_hARRIS, #wintype
0, #fc
samp_rate, #bw
"Raw Spectrum", #name
1)
self.qtgui_freq_sink_x_2.set_update_time(0.10)
self.qtgui_freq_sink_x_2.set_y_axis(-140, 10)
self.qtgui_freq_sink_x_2.set_y_label('Relative Gain', 'dB')
self.qtgui_freq_sink_x_2.set_trigger_mode(qtgui.TRIG_MODE_FREE, 0.0, 0,
"")
self.qtgui_freq_sink_x_2.enable_autoscale(False)
self.qtgui_freq_sink_x_2.enable_grid(False)
self.qtgui_freq_sink_x_2.set_fft_average(1.0)
self.qtgui_freq_sink_x_2.enable_axis_labels(True)
self.qtgui_freq_sink_x_2.enable_control_panel(False)
labels = ['', '', '', '', '', '', '', '', '', '']
widths = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
colors = [
"blue", "red", "green", "black", "cyan", "magenta", "yellow",
"dark red", "dark green", "dark blue"
]
alphas = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
for i in range(1):
if len(labels[i]) == 0:
self.qtgui_freq_sink_x_2.set_line_label(
i, "Data {0}".format(i))
else:
self.qtgui_freq_sink_x_2.set_line_label(i, labels[i])
self.qtgui_freq_sink_x_2.set_line_width(i, widths[i])
self.qtgui_freq_sink_x_2.set_line_color(i, colors[i])
self.qtgui_freq_sink_x_2.set_line_alpha(i, alphas[i])
self._qtgui_freq_sink_x_2_win = sip.wrapinstance(
self.qtgui_freq_sink_x_2.pyqwidget(), Qt.QWidget)
self.top_grid_layout.addWidget(self._qtgui_freq_sink_x_2_win)
self.qtgui_freq_sink_x_1 = qtgui.freq_sink_c(
1024, #size
firdes.WIN_BLACKMAN_hARRIS, #wintype
0, #fc
samp_rate, #bw
"Filtered GA Spectrum", #name
1)
self.qtgui_freq_sink_x_1.set_update_time(0.10)
self.qtgui_freq_sink_x_1.set_y_axis(-140, 10)
self.qtgui_freq_sink_x_1.set_y_label('Relative Gain', 'dB')
self.qtgui_freq_sink_x_1.set_trigger_mode(qtgui.TRIG_MODE_FREE, 0.0, 0,
"")
self.qtgui_freq_sink_x_1.enable_autoscale(False)
self.qtgui_freq_sink_x_1.enable_grid(False)
self.qtgui_freq_sink_x_1.set_fft_average(1.0)
self.qtgui_freq_sink_x_1.enable_axis_labels(True)
self.qtgui_freq_sink_x_1.enable_control_panel(False)
labels = ['', '', '', '', '', '', '', '', '', '']
widths = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
colors = [
"blue", "red", "green", "black", "cyan", "magenta", "yellow",
"dark red", "dark green", "dark blue"
]
alphas = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
for i in range(1):
if len(labels[i]) == 0:
self.qtgui_freq_sink_x_1.set_line_label(
i, "Data {0}".format(i))
else:
self.qtgui_freq_sink_x_1.set_line_label(i, labels[i])
self.qtgui_freq_sink_x_1.set_line_width(i, widths[i])
self.qtgui_freq_sink_x_1.set_line_color(i, colors[i])
self.qtgui_freq_sink_x_1.set_line_alpha(i, alphas[i])
self._qtgui_freq_sink_x_1_win = sip.wrapinstance(
self.qtgui_freq_sink_x_1.pyqwidget(), Qt.QWidget)
self.top_grid_layout.addWidget(self._qtgui_freq_sink_x_1_win)
self.qtgui_freq_sink_x_0 = qtgui.freq_sink_c(
1024, #size
firdes.WIN_BLACKMAN_hARRIS, #wintype
0, #fc
samp_rate / decimation, #bw
"Filtered Spectrum", #name
1)
self.qtgui_freq_sink_x_0.set_update_time(0.10)
self.qtgui_freq_sink_x_0.set_y_axis(-140, 10)
self.qtgui_freq_sink_x_0.set_y_label('Relative Gain', 'dB')
self.qtgui_freq_sink_x_0.set_trigger_mode(qtgui.TRIG_MODE_FREE, 0.0, 0,
"")
self.qtgui_freq_sink_x_0.enable_autoscale(False)
self.qtgui_freq_sink_x_0.enable_grid(False)
self.qtgui_freq_sink_x_0.set_fft_average(1.0)
self.qtgui_freq_sink_x_0.enable_axis_labels(True)
self.qtgui_freq_sink_x_0.enable_control_panel(False)
labels = ['', '', '', '', '', '', '', '', '', '']
widths = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
colors = [
"blue", "red", "green", "black", "cyan", "magenta", "yellow",
"dark red", "dark green", "dark blue"
]
alphas = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
for i in range(1):
if len(labels[i]) == 0:
self.qtgui_freq_sink_x_0.set_line_label(
i, "Data {0}".format(i))
else:
self.qtgui_freq_sink_x_0.set_line_label(i, labels[i])
self.qtgui_freq_sink_x_0.set_line_width(i, widths[i])
self.qtgui_freq_sink_x_0.set_line_color(i, colors[i])
self.qtgui_freq_sink_x_0.set_line_alpha(i, alphas[i])
self._qtgui_freq_sink_x_0_win = sip.wrapinstance(
self.qtgui_freq_sink_x_0.pyqwidget(), Qt.QWidget)
self.top_grid_layout.addWidget(self._qtgui_freq_sink_x_0_win)
self.freq_xlating_fir_filter_xxx_0 = filter.freq_xlating_fir_filter_ccc(
decimation,
firdes.low_pass(1, samp_rate, 10e3, 1e3, firdes.WIN_HAMMING, 6.76),
-53e3, samp_rate)
self._clock_freq_range = Range(1e3, 1e5, 1, 1e3, 200)
self._clock_freq_win = RangeWidget(self._clock_freq_range,
self.set_clock_freq,
'Clock Frequency', "counter_slider",
float)
self.top_grid_layout.addWidget(self._clock_freq_win)
self.blocks_threshold_ff_0 = blocks.threshold_ff(0.5, 0.5, 0)
self.blocks_peak_detector_xb_0 = blocks.peak_detector_fb(
0.25, 0.40, 10, 0.001)
self.blocks_moving_average_xx_0 = blocks.moving_average_ff(
5, 1, 4000, 1)
self.blocks_complex_to_mag_squared_0 = blocks.complex_to_mag_squared(1)
self.blocks_char_to_short_0 = blocks.char_to_short(1)
self.blocks_burst_tagger_0 = blocks.burst_tagger(gr.sizeof_float)
self.blocks_burst_tagger_0.set_true_tag('burst', True)
self.blocks_burst_tagger_0.set_false_tag('burst', False)
##################################################
# Connections
##################################################
self.connect((self.blocks_burst_tagger_0, 0),
(self.qtgui_time_sink_x_0, 0))
self.connect((self.blocks_char_to_short_0, 0),
(self.blocks_burst_tagger_0, 1))
self.connect((self.blocks_complex_to_mag_squared_0, 0),
(self.blocks_moving_average_xx_0, 0))
self.connect((self.blocks_moving_average_xx_0, 0),
(self.blocks_threshold_ff_0, 0))
self.connect((self.blocks_peak_detector_xb_0, 0),
(self.blocks_char_to_short_0, 0))
self.connect((self.blocks_threshold_ff_0, 0),
(self.blocks_burst_tagger_0, 0))
self.connect((self.blocks_threshold_ff_0, 0),
(self.blocks_peak_detector_xb_0, 0))
self.connect((self.blocks_threshold_ff_0, 0),
(self.qtgui_time_sink_x_1_0, 0))
self.connect((self.freq_xlating_fir_filter_xxx_0, 0),
(self.blocks_complex_to_mag_squared_0, 0))
self.connect((self.freq_xlating_fir_filter_xxx_0, 0),
(self.qtgui_freq_sink_x_0, 0))
self.connect((self.freq_xlating_fir_filter_xxx_0, 0),
(self.qtgui_freq_sink_x_1, 0))
self.connect((self.rtlsdr_source_0, 0),
(self.freq_xlating_fir_filter_xxx_0, 0))
self.connect((self.rtlsdr_source_0, 0), (self.qtgui_freq_sink_x_2, 0))
def __init__(self, subdev="A:0", devid="addr=192.168.10.2", frequency=1.4125e9, fftsize=8192):
grc_wxgui.top_block_gui.__init__(self, title="Total Power Radiometer - N200")
##################################################
# Parameters
##################################################
self.subdev = subdev
self.devid = devid
self.frequency = frequency
self.fftsize = fftsize
##################################################
# Variables
##################################################
self.GUI_samp_rate = GUI_samp_rate = 10e6
self.samp_rate = samp_rate = int(GUI_samp_rate)
self.prefix = prefix = "tpr_"
self.text_samp_rate = text_samp_rate = GUI_samp_rate
self.text_deviceID = text_deviceID = subdev
self.text_Device_addr = text_Device_addr = devid
self.spec_data_fifo = spec_data_fifo = "spectrum_" + datetime.now().strftime("%Y.%m.%d.%H.%M.%S") + ".dat"
self.spavg = spavg = 1
self.scope_rate = scope_rate = 2
self.recfile_tpr = recfile_tpr = prefix + datetime.now().strftime("%Y.%m.%d.%H.%M.%S") + ".dat"
self.recfile_kelvin = recfile_kelvin = prefix+"kelvin" + datetime.now().strftime("%Y.%m.%d.%H.%M.%S") + ".dat"
self.rec_button_tpr = rec_button_tpr = 1
self.rec_button_iq = rec_button_iq = 1
self.noise_amplitude = noise_amplitude = .5
self.integ = integ = 2
self.gain = gain = 26
self.freq = freq = frequency
self.file_rate = file_rate = 2.0
self.fftrate = fftrate = int(samp_rate/fftsize)
self.det_rate = det_rate = int(20.0)
self.dc_gain = dc_gain = 1
self.calib_2 = calib_2 = -342.774
self.calib_1 = calib_1 = 4.0755e3
self.add_noise = add_noise = 0
##################################################
# Blocks
##################################################
self.Main = self.Main = wx.Notebook(self.GetWin(), style=wx.NB_TOP)
self.Main.AddPage(grc_wxgui.Panel(self.Main), "N200 Control Panel")
self.Main.AddPage(grc_wxgui.Panel(self.Main), "TPR Measurements")
self.Add(self.Main)
_spavg_sizer = wx.BoxSizer(wx.VERTICAL)
self._spavg_text_box = forms.text_box(
parent=self.Main.GetPage(0).GetWin(),
sizer=_spavg_sizer,
value=self.spavg,
callback=self.set_spavg,
label="Spectral Averaging (Seconds)",
converter=forms.int_converter(),
proportion=0,
)
self._spavg_slider = forms.slider(
parent=self.Main.GetPage(0).GetWin(),
sizer=_spavg_sizer,
value=self.spavg,
callback=self.set_spavg,
minimum=1,
maximum=20,
num_steps=20,
style=wx.SL_HORIZONTAL,
cast=int,
proportion=1,
)
self.Main.GetPage(0).GridAdd(_spavg_sizer, 1, 1, 1, 1)
self._rec_button_tpr_chooser = forms.button(
parent=self.Main.GetPage(0).GetWin(),
value=self.rec_button_tpr,
callback=self.set_rec_button_tpr,
label="Record TPR Data",
choices=[0,1],
labels=['Stop','Start'],
)
self.Main.GetPage(0).GridAdd(self._rec_button_tpr_chooser, 4, 1, 1, 1)
self._rec_button_iq_chooser = forms.button(
parent=self.Main.GetPage(0).GetWin(),
value=self.rec_button_iq,
callback=self.set_rec_button_iq,
label="Record I/Q Data",
choices=[0,1],
labels=['Stop','Start'],
)
self.Main.GetPage(0).GridAdd(self._rec_button_iq_chooser, 4, 0, 1, 1)
_integ_sizer = wx.BoxSizer(wx.VERTICAL)
self._integ_text_box = forms.text_box(
parent=self.Main.GetPage(0).GetWin(),
sizer=_integ_sizer,
value=self.integ,
callback=self.set_integ,
label="Integration Time (Seconds)",
converter=forms.float_converter(),
proportion=0,
)
self._integ_slider = forms.slider(
parent=self.Main.GetPage(0).GetWin(),
sizer=_integ_sizer,
value=self.integ,
callback=self.set_integ,
minimum=1,
maximum=60,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.Main.GetPage(0).GridAdd(_integ_sizer, 0, 2, 1, 1)
_gain_sizer = wx.BoxSizer(wx.VERTICAL)
self._gain_text_box = forms.text_box(
parent=self.Main.GetPage(0).GetWin(),
sizer=_gain_sizer,
value=self.gain,
callback=self.set_gain,
label="RF Gain (dB)",
converter=forms.float_converter(),
proportion=0,
)
self._gain_slider = forms.slider(
parent=self.Main.GetPage(0).GetWin(),
sizer=_gain_sizer,
value=self.gain,
callback=self.set_gain,
minimum=0,
maximum=50,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.Main.GetPage(0).GridAdd(_gain_sizer, 0, 1, 1, 1)
self._freq_text_box = forms.text_box(
parent=self.Main.GetPage(0).GetWin(),
value=self.freq,
callback=self.set_freq,
label="Center Frequency (Hz)",
converter=forms.float_converter(),
)
self.Main.GetPage(0).GridAdd(self._freq_text_box, 0, 0, 1, 1)
self._dc_gain_chooser = forms.radio_buttons(
parent=self.Main.GetPage(0).GetWin(),
value=self.dc_gain,
callback=self.set_dc_gain,
label="DC Gain",
choices=[1, 10, 100, 1000, 10000],
labels=[],
style=wx.RA_HORIZONTAL,
)
self.Main.GetPage(0).GridAdd(self._dc_gain_chooser, 1, 0, 1, 1)
self._calib_2_text_box = forms.text_box(
parent=self.Main.GetPage(0).GetWin(),
value=self.calib_2,
callback=self.set_calib_2,
label="Calibration value 2",
converter=forms.float_converter(),
)
self.Main.GetPage(0).GridAdd(self._calib_2_text_box, 3, 1, 1, 1)
self._calib_1_text_box = forms.text_box(
parent=self.Main.GetPage(0).GetWin(),
value=self.calib_1,
callback=self.set_calib_1,
label="Calibration value 1",
converter=forms.float_converter(),
)
self.Main.GetPage(0).GridAdd(self._calib_1_text_box, 3, 0, 1, 1)
self._GUI_samp_rate_chooser = forms.radio_buttons(
parent=self.Main.GetPage(0).GetWin(),
value=self.GUI_samp_rate,
callback=self.set_GUI_samp_rate,
label="Sample Rate (BW)",
choices=[1e6,2e6,5e6,10e6,25e6],
labels=['1 MHz','2 MHz','5 MHz','10 MHz','25 MHz'],
style=wx.RA_HORIZONTAL,
)
self.Main.GetPage(0).GridAdd(self._GUI_samp_rate_chooser, 1, 3, 1, 1)
self.wxgui_scopesink2_2 = scopesink2.scope_sink_f(
self.Main.GetPage(1).GetWin(),
title="Total Power",
sample_rate=2,
v_scale=.1,
v_offset=0,
t_scale=100,
ac_couple=False,
xy_mode=False,
num_inputs=1,
trig_mode=wxgui.TRIG_MODE_STRIPCHART,
y_axis_label="power level",
)
self.Main.GetPage(1).Add(self.wxgui_scopesink2_2.win)
self.wxgui_numbersink2_2 = numbersink2.number_sink_f(
self.GetWin(),
unit="Units",
minval=0,
maxval=1,
factor=1.0,
decimal_places=10,
ref_level=0,
sample_rate=GUI_samp_rate,
number_rate=15,
average=False,
avg_alpha=None,
label="Number Plot",
peak_hold=False,
show_gauge=True,
)
self.Add(self.wxgui_numbersink2_2.win)
self.wxgui_numbersink2_0_0 = numbersink2.number_sink_f(
self.Main.GetPage(1).GetWin(),
unit="",
minval=0,
maxval=.2,
factor=1,
decimal_places=6,
ref_level=0,
sample_rate=scope_rate,
number_rate=15,
average=True,
avg_alpha=.01,
label="Raw Power level",
peak_hold=False,
show_gauge=True,
)
self.Main.GetPage(1).Add(self.wxgui_numbersink2_0_0.win)
self.wxgui_numbersink2_0 = numbersink2.number_sink_f(
self.Main.GetPage(1).GetWin(),
unit="Kelvin",
minval=0,
maxval=400,
factor=1,
decimal_places=6,
ref_level=0,
sample_rate=scope_rate,
number_rate=15,
average=False,
avg_alpha=None,
label="Calibrated Temperature",
peak_hold=False,
show_gauge=True,
)
self.Main.GetPage(1).Add(self.wxgui_numbersink2_0.win)
self.wxgui_fftsink2_0 = fftsink2.fft_sink_c(
self.Main.GetPage(0).GetWin(),
baseband_freq=freq,
y_per_div=10,
y_divs=10,
ref_level=20,
ref_scale=2.0,
sample_rate=GUI_samp_rate,
fft_size=1024,
fft_rate=5,
average=True,
avg_alpha=0.1,
title="Spectrum",
peak_hold=False,
size=(800,400),
)
self.Main.GetPage(0).Add(self.wxgui_fftsink2_0.win)
self.uhd_usrp_source_0 = uhd.usrp_source(
",".join((devid, "")),
uhd.stream_args(
cpu_format="fc32",
channels=range(1),
),
)
self.uhd_usrp_source_0.set_samp_rate(GUI_samp_rate)
self.uhd_usrp_source_0.set_center_freq(freq, 0)
self.uhd_usrp_source_0.set_gain(gain, 0)
(self.uhd_usrp_source_0).set_processor_affinity([0])
self._text_samp_rate_static_text = forms.static_text(
parent=self.Main.GetPage(0).GetWin(),
value=self.text_samp_rate,
callback=self.set_text_samp_rate,
label="Samp rate",
converter=forms.float_converter(),
)
self.Main.GetPage(0).GridAdd(self._text_samp_rate_static_text, 2, 0, 1, 1)
self._text_deviceID_static_text = forms.static_text(
parent=self.Main.GetPage(0).GetWin(),
value=self.text_deviceID,
callback=self.set_text_deviceID,
label="SubDev",
converter=forms.str_converter(),
)
self.Main.GetPage(0).GridAdd(self._text_deviceID_static_text, 2, 1, 1, 1)
self._text_Device_addr_static_text = forms.static_text(
parent=self.Main.GetPage(0).GetWin(),
value=self.text_Device_addr,
callback=self.set_text_Device_addr,
label="Device Address",
converter=forms.str_converter(),
)
self.Main.GetPage(0).GridAdd(self._text_Device_addr_static_text, 2, 2, 1, 1)
self.single_pole_iir_filter_xx_0 = filter.single_pole_iir_filter_ff(1.0/((samp_rate*integ)/2.0), 1)
(self.single_pole_iir_filter_xx_0).set_processor_affinity([1])
_noise_amplitude_sizer = wx.BoxSizer(wx.VERTICAL)
self._noise_amplitude_text_box = forms.text_box(
parent=self.Main.GetPage(0).GetWin(),
sizer=_noise_amplitude_sizer,
value=self.noise_amplitude,
callback=self.set_noise_amplitude,
label='noise_amplitude',
converter=forms.float_converter(),
proportion=0,
)
self._noise_amplitude_slider = forms.slider(
parent=self.Main.GetPage(0).GetWin(),
sizer=_noise_amplitude_sizer,
value=self.noise_amplitude,
callback=self.set_noise_amplitude,
minimum=.01,
maximum=1,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.Main.GetPage(0).GridAdd(_noise_amplitude_sizer, 3, 2, 1, 1)
self.logpwrfft_x_0 = logpwrfft.logpwrfft_c(
sample_rate=samp_rate,
fft_size=fftsize,
ref_scale=2,
frame_rate=fftrate,
avg_alpha=1.0/float(spavg*fftrate),
average=True,
)
self.blocks_peak_detector_xb_0 = blocks.peak_detector_fb(0.25, 0.40, 10, 0.001)
self.blocks_multiply_const_vxx_1 = blocks.multiply_const_vff((calib_1, ))
self.blocks_multiply_const_vxx_0 = blocks.multiply_const_vff((dc_gain, ))
self.blocks_keep_one_in_n_4 = blocks.keep_one_in_n(gr.sizeof_float*1, samp_rate/det_rate)
self.blocks_keep_one_in_n_3 = blocks.keep_one_in_n(gr.sizeof_float*fftsize, fftrate)
self.blocks_keep_one_in_n_1 = blocks.keep_one_in_n(gr.sizeof_float*1, int(det_rate/file_rate))
self.blocks_file_sink_5 = blocks.file_sink(gr.sizeof_float*fftsize, spec_data_fifo, False)
self.blocks_file_sink_5.set_unbuffered(True)
self.blocks_file_sink_4 = blocks.file_sink(gr.sizeof_float*1, recfile_tpr, False)
self.blocks_file_sink_4.set_unbuffered(True)
self.blocks_file_sink_1 = blocks.file_sink(gr.sizeof_gr_complex*1, prefix+"iq_raw" + datetime.now().strftime("%Y.%m.%d.%H.%M.%S") + ".dat", False)
self.blocks_file_sink_1.set_unbuffered(False)
self.blocks_file_sink_0 = blocks.file_sink(gr.sizeof_float*1, recfile_kelvin, False)
self.blocks_file_sink_0.set_unbuffered(True)
self.blocks_complex_to_real_0 = blocks.complex_to_real(1)
self.blocks_complex_to_mag_squared_1 = blocks.complex_to_mag_squared(1)
self.blocks_char_to_float_0 = blocks.char_to_float(1, 1)
self.blocks_add_const_vxx_1 = blocks.add_const_vff((calib_2, ))
self.blks2_valve_2 = grc_blks2.valve(item_size=gr.sizeof_gr_complex*1, open=bool(rec_button_iq))
self.blks2_valve_1 = grc_blks2.valve(item_size=gr.sizeof_float*1, open=bool(0))
self.blks2_valve_0 = grc_blks2.valve(item_size=gr.sizeof_float*1, open=bool(rec_button_tpr))
self._add_noise_chooser = forms.button(
parent=self.Main.GetPage(0).GetWin(),
value=self.add_noise,
callback=self.set_add_noise,
label="Noise Source",
choices=[0,1],
labels=['Off','On'],
)
self.Main.GetPage(0).GridAdd(self._add_noise_chooser, 3, 3, 1, 1)
##################################################
# Connections
##################################################
self.connect((self.blks2_valve_0, 0), (self.blocks_file_sink_4, 0))
self.connect((self.blks2_valve_1, 0), (self.blocks_file_sink_0, 0))
self.connect((self.blks2_valve_2, 0), (self.blocks_file_sink_1, 0))
self.connect((self.blocks_add_const_vxx_1, 0), (self.blks2_valve_1, 0))
self.connect((self.blocks_add_const_vxx_1, 0), (self.wxgui_numbersink2_0, 0))
self.connect((self.blocks_char_to_float_0, 0), (self.wxgui_numbersink2_2, 0))
self.connect((self.blocks_complex_to_mag_squared_1, 0), (self.single_pole_iir_filter_xx_0, 0))
self.connect((self.blocks_complex_to_real_0, 0), (self.blocks_peak_detector_xb_0, 0))
self.connect((self.blocks_keep_one_in_n_1, 0), (self.blks2_valve_0, 0))
self.connect((self.blocks_keep_one_in_n_1, 0), (self.blocks_multiply_const_vxx_1, 0))
self.connect((self.blocks_keep_one_in_n_1, 0), (self.wxgui_scopesink2_2, 0))
self.connect((self.blocks_keep_one_in_n_3, 0), (self.blocks_file_sink_5, 0))
self.connect((self.blocks_keep_one_in_n_4, 0), (self.blocks_multiply_const_vxx_0, 0))
self.connect((self.blocks_multiply_const_vxx_0, 0), (self.blocks_keep_one_in_n_1, 0))
self.connect((self.blocks_multiply_const_vxx_0, 0), (self.wxgui_numbersink2_0_0, 0))
self.connect((self.blocks_multiply_const_vxx_1, 0), (self.blocks_add_const_vxx_1, 0))
self.connect((self.blocks_peak_detector_xb_0, 0), (self.blocks_char_to_float_0, 0))
self.connect((self.logpwrfft_x_0, 0), (self.blocks_keep_one_in_n_3, 0))
self.connect((self.single_pole_iir_filter_xx_0, 0), (self.blocks_keep_one_in_n_4, 0))
self.connect((self.uhd_usrp_source_0, 0), (self.blks2_valve_2, 0))
self.connect((self.uhd_usrp_source_0, 0), (self.blocks_complex_to_mag_squared_1, 0))
self.connect((self.uhd_usrp_source_0, 0), (self.blocks_complex_to_real_0, 0))
self.connect((self.uhd_usrp_source_0, 0), (self.logpwrfft_x_0, 0))
self.connect((self.uhd_usrp_source_0, 0), (self.wxgui_fftsink2_0, 0))
def __init__(self):
gr.top_block.__init__(self, "Not titled yet")
Qt.QWidget.__init__(self)
self.setWindowTitle("Not titled yet")
qtgui.util.check_set_qss()
try:
self.setWindowIcon(Qt.QIcon.fromTheme('gnuradio-grc'))
except:
pass
self.top_scroll_layout = Qt.QVBoxLayout()
self.setLayout(self.top_scroll_layout)
self.top_scroll = Qt.QScrollArea()
self.top_scroll.setFrameStyle(Qt.QFrame.NoFrame)
self.top_scroll_layout.addWidget(self.top_scroll)
self.top_scroll.setWidgetResizable(True)
self.top_widget = Qt.QWidget()
self.top_scroll.setWidget(self.top_widget)
self.top_layout = Qt.QVBoxLayout(self.top_widget)
self.top_grid_layout = Qt.QGridLayout()
self.top_layout.addLayout(self.top_grid_layout)
self.settings = Qt.QSettings("GNU Radio", "clock_recovery")
try:
if StrictVersion(Qt.qVersion()) < StrictVersion("5.0.0"):
self.restoreGeometry(
self.settings.value("geometry").toByteArray())
else:
self.restoreGeometry(self.settings.value("geometry"))
except:
pass
##################################################
# Variables
##################################################
self.xlate_freq = xlate_freq = -223
self.trans_width = trans_width = 20e3
self.samp_rate = samp_rate = 2048e3
self.samp_per_sym = samp_per_sym = 10
self.filter_freq = filter_freq = 80e3
self.decimation = decimation = 1
##################################################
# Blocks
##################################################
self._xlate_freq_range = Range(-10000, +10000, 1, -223, 200)
self._xlate_freq_win = RangeWidget(self._xlate_freq_range,
self.set_xlate_freq,
'Translating Frequency',
"counter_slider", float)
self.top_grid_layout.addWidget(self._xlate_freq_win)
self._trans_width_range = Range(1e3, 100e3, 1e3, 20e3, 200)
self._trans_width_win = RangeWidget(self._trans_width_range,
self.set_trans_width,
'Transition Width',
"counter_slider", float)
self.top_grid_layout.addWidget(self._trans_width_win)
self._filter_freq_range = Range(20e3, 500e3, 1e3, 80e3, 200)
self._filter_freq_win = RangeWidget(self._filter_freq_range,
self.set_filter_freq,
'Filter Frequency',
"counter_slider", float)
self.top_grid_layout.addWidget(self._filter_freq_win)
self.qtgui_time_sink_x_3 = qtgui.time_sink_f(
1024, #size
samp_rate, #samp_rate
"", #name
1 #number of inputs
)
self.qtgui_time_sink_x_3.set_update_time(0.10)
self.qtgui_time_sink_x_3.set_y_axis(-1, 1)
self.qtgui_time_sink_x_3.set_y_label('Amplitude', "")
self.qtgui_time_sink_x_3.enable_tags(True)
self.qtgui_time_sink_x_3.set_trigger_mode(qtgui.TRIG_MODE_FREE,
qtgui.TRIG_SLOPE_POS, 0.0, 0,
0, "")
self.qtgui_time_sink_x_3.enable_autoscale(False)
self.qtgui_time_sink_x_3.enable_grid(False)
self.qtgui_time_sink_x_3.enable_axis_labels(True)
self.qtgui_time_sink_x_3.enable_control_panel(True)
self.qtgui_time_sink_x_3.enable_stem_plot(False)
labels = [
'Signal 1', 'Signal 2', 'Signal 3', 'Signal 4', 'Signal 5',
'Signal 6', 'Signal 7', 'Signal 8', 'Signal 9', 'Signal 10'
]
widths = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
colors = [
'blue', 'red', 'green', 'black', 'cyan', 'magenta', 'yellow',
'dark red', 'dark green', 'dark blue'
]
alphas = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
styles = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
markers = [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
for i in range(1):
if len(labels[i]) == 0:
self.qtgui_time_sink_x_3.set_line_label(
i, "Data {0}".format(i))
else:
self.qtgui_time_sink_x_3.set_line_label(i, labels[i])
self.qtgui_time_sink_x_3.set_line_width(i, widths[i])
self.qtgui_time_sink_x_3.set_line_color(i, colors[i])
self.qtgui_time_sink_x_3.set_line_style(i, styles[i])
self.qtgui_time_sink_x_3.set_line_marker(i, markers[i])
self.qtgui_time_sink_x_3.set_line_alpha(i, alphas[i])
self._qtgui_time_sink_x_3_win = sip.wrapinstance(
self.qtgui_time_sink_x_3.pyqwidget(), Qt.QWidget)
self.top_grid_layout.addWidget(self._qtgui_time_sink_x_3_win)
self.qtgui_time_sink_x_0 = qtgui.time_sink_c(
1024, #size
samp_rate, #samp_rate
'Xlated Signal', #name
1 #number of inputs
)
self.qtgui_time_sink_x_0.set_update_time(0.10)
self.qtgui_time_sink_x_0.set_y_axis(-1, 1)
self.qtgui_time_sink_x_0.set_y_label('Amplitude', "")
self.qtgui_time_sink_x_0.enable_tags(True)
self.qtgui_time_sink_x_0.set_trigger_mode(qtgui.TRIG_MODE_FREE,
qtgui.TRIG_SLOPE_POS, 0.0, 0,
0, "")
self.qtgui_time_sink_x_0.enable_autoscale(False)
self.qtgui_time_sink_x_0.enable_grid(False)
self.qtgui_time_sink_x_0.enable_axis_labels(True)
self.qtgui_time_sink_x_0.enable_control_panel(False)
self.qtgui_time_sink_x_0.enable_stem_plot(False)
labels = [
'Signal 1', 'Signal 2', 'Signal 3', 'Signal 4', 'Signal 5',
'Signal 6', 'Signal 7', 'Signal 8', 'Signal 9', 'Signal 10'
]
widths = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
colors = [
'blue', 'red', 'green', 'black', 'cyan', 'magenta', 'yellow',
'dark red', 'dark green', 'dark blue'
]
alphas = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
styles = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
markers = [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
for i in range(2):
if len(labels[i]) == 0:
if (i % 2 == 0):
self.qtgui_time_sink_x_0.set_line_label(
i, "Re{{Data {0}}}".format(i / 2))
else:
self.qtgui_time_sink_x_0.set_line_label(
i, "Im{{Data {0}}}".format(i / 2))
else:
self.qtgui_time_sink_x_0.set_line_label(i, labels[i])
self.qtgui_time_sink_x_0.set_line_width(i, widths[i])
self.qtgui_time_sink_x_0.set_line_color(i, colors[i])
self.qtgui_time_sink_x_0.set_line_style(i, styles[i])
self.qtgui_time_sink_x_0.set_line_marker(i, markers[i])
self.qtgui_time_sink_x_0.set_line_alpha(i, alphas[i])
self._qtgui_time_sink_x_0_win = sip.wrapinstance(
self.qtgui_time_sink_x_0.pyqwidget(), Qt.QWidget)
self.top_grid_layout.addWidget(self._qtgui_time_sink_x_0_win)
self.qtgui_freq_sink_x_0 = qtgui.freq_sink_c(
1024, #size
firdes.WIN_BLACKMAN_hARRIS, #wintype
0, #fc
samp_rate, #bw
'Xlated Signal', #name
1)
self.qtgui_freq_sink_x_0.set_update_time(0.10)
self.qtgui_freq_sink_x_0.set_y_axis(-140, 10)
self.qtgui_freq_sink_x_0.set_y_label('Relative Gain', 'dB')
self.qtgui_freq_sink_x_0.set_trigger_mode(qtgui.TRIG_MODE_FREE, 0.0, 0,
"")
self.qtgui_freq_sink_x_0.enable_autoscale(False)
self.qtgui_freq_sink_x_0.enable_grid(False)
self.qtgui_freq_sink_x_0.set_fft_average(1.0)
self.qtgui_freq_sink_x_0.enable_axis_labels(True)
self.qtgui_freq_sink_x_0.enable_control_panel(True)
labels = ['', '', '', '', '', '', '', '', '', '']
widths = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
colors = [
"blue", "red", "green", "black", "cyan", "magenta", "yellow",
"dark red", "dark green", "dark blue"
]
alphas = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
for i in range(1):
if len(labels[i]) == 0:
self.qtgui_freq_sink_x_0.set_line_label(
i, "Data {0}".format(i))
else:
self.qtgui_freq_sink_x_0.set_line_label(i, labels[i])
self.qtgui_freq_sink_x_0.set_line_width(i, widths[i])
self.qtgui_freq_sink_x_0.set_line_color(i, colors[i])
self.qtgui_freq_sink_x_0.set_line_alpha(i, alphas[i])
self._qtgui_freq_sink_x_0_win = sip.wrapinstance(
self.qtgui_freq_sink_x_0.pyqwidget(), Qt.QWidget)
self.top_grid_layout.addWidget(self._qtgui_freq_sink_x_0_win)
self.freq_xlating_fir_filter_xxx_0 = filter.freq_xlating_fir_filter_ccc(
decimation,
firdes.low_pass(1, samp_rate, filter_freq, trans_width,
firdes.WIN_HAMMING, 6.76), xlate_freq, samp_rate)
self.digital_clock_recovery_mm_xx_0 = digital.clock_recovery_mm_ff(
samp_per_sym * (1 + 0.0), 0.25 * 0.175 * 0.175, 0.5, 0.175, 0.005)
self.digital_binary_slicer_fb_0_0 = digital.binary_slicer_fb()
self.digital_binary_slicer_fb_0 = digital.binary_slicer_fb()
self.blocks_uchar_to_float_1 = blocks.uchar_to_float()
self.blocks_uchar_to_float_0 = blocks.uchar_to_float()
self.blocks_threshold_ff_0 = blocks.threshold_ff(0.1, 0.1, 0)
self.blocks_peak_detector_xb_0 = blocks.peak_detector_fb(
0.25, 0.40, 10, 0.001)
self.blocks_multiply_const_vxx_0_0 = blocks.multiply_const_ff(1 / 255)
self.blocks_multiply_const_vxx_0 = blocks.multiply_const_ff(1 / 255)
self.blocks_float_to_complex_0 = blocks.float_to_complex(1)
self.blocks_file_source_0 = blocks.file_source(
gr.sizeof_char * 1,
'/Users/bodokaiser/Repositories/github.com/bodokaiser/arduino-rtlsdr/reverse-engineering/data/10111_11111.cu8',
True, 0, 0)
self.blocks_file_source_0.set_begin_tag(pmt.PMT_NIL)
self.blocks_deinterleave_0 = blocks.deinterleave(gr.sizeof_char * 1, 1)
self.blocks_complex_to_mag_squared_0 = blocks.complex_to_mag_squared(1)
self.blocks_char_to_short_0 = blocks.char_to_short(1)
self.blocks_char_to_float_0 = blocks.char_to_float(1, 1)
self.blocks_burst_tagger_0 = blocks.burst_tagger(gr.sizeof_float)
self.blocks_burst_tagger_0.set_true_tag('burst', True)
self.blocks_burst_tagger_0.set_false_tag('burst', False)
self.blocks_and_xx_0 = blocks.and_bb()
self.blocks_add_const_vxx_1 = blocks.add_const_ff(-0.5)
self.blocks_add_const_vxx_0 = blocks.add_const_ff(-0.5)
##################################################
# Connections
##################################################
self.connect((self.blocks_add_const_vxx_0, 0),
(self.blocks_float_to_complex_0, 0))
self.connect((self.blocks_add_const_vxx_1, 0),
(self.blocks_float_to_complex_0, 1))
self.connect((self.blocks_and_xx_0, 0),
(self.blocks_char_to_float_0, 0))
self.connect((self.blocks_burst_tagger_0, 0),
(self.digital_binary_slicer_fb_0_0, 0))
self.connect((self.blocks_burst_tagger_0, 0),
(self.digital_clock_recovery_mm_xx_0, 0))
self.connect((self.blocks_char_to_float_0, 0),
(self.qtgui_time_sink_x_3, 0))
self.connect((self.blocks_char_to_short_0, 0),
(self.blocks_burst_tagger_0, 1))
self.connect((self.blocks_complex_to_mag_squared_0, 0),
(self.blocks_threshold_ff_0, 0))
self.connect((self.blocks_deinterleave_0, 0),
(self.blocks_uchar_to_float_0, 0))
self.connect((self.blocks_deinterleave_0, 1),
(self.blocks_uchar_to_float_1, 0))
self.connect((self.blocks_file_source_0, 0),
(self.blocks_deinterleave_0, 0))
self.connect((self.blocks_float_to_complex_0, 0),
(self.freq_xlating_fir_filter_xxx_0, 0))
self.connect((self.blocks_multiply_const_vxx_0, 0),
(self.blocks_add_const_vxx_0, 0))
self.connect((self.blocks_multiply_const_vxx_0_0, 0),
(self.blocks_add_const_vxx_1, 0))
self.connect((self.blocks_peak_detector_xb_0, 0),
(self.blocks_char_to_short_0, 0))
self.connect((self.blocks_threshold_ff_0, 0),
(self.blocks_burst_tagger_0, 0))
self.connect((self.blocks_threshold_ff_0, 0),
(self.blocks_peak_detector_xb_0, 0))
self.connect((self.blocks_uchar_to_float_0, 0),
(self.blocks_multiply_const_vxx_0, 0))
self.connect((self.blocks_uchar_to_float_1, 0),
(self.blocks_multiply_const_vxx_0_0, 0))
self.connect((self.digital_binary_slicer_fb_0, 0),
(self.blocks_and_xx_0, 1))
self.connect((self.digital_binary_slicer_fb_0_0, 0),
(self.blocks_and_xx_0, 0))
self.connect((self.digital_clock_recovery_mm_xx_0, 0),
(self.digital_binary_slicer_fb_0, 0))
self.connect((self.freq_xlating_fir_filter_xxx_0, 0),
(self.blocks_complex_to_mag_squared_0, 0))
self.connect((self.freq_xlating_fir_filter_xxx_0, 0),
(self.qtgui_freq_sink_x_0, 0))
self.connect((self.freq_xlating_fir_filter_xxx_0, 0),
(self.qtgui_time_sink_x_0, 0))
