kopia lustrzana https://github.com/projecthorus/radiosonde_auto_rx
133 wiersze
4.1 KiB
Python
133 wiersze
4.1 KiB
Python
#!/usr/bin/env python
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#
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# Generate Noisy Sonde Samples, with a calibrated Eb/No
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#
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# Run from ./scripts/ with
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# $ python generate_lowsnr.py
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#
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# The generated files will end up in the 'generated' directory.
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#
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# Copyright (C) 2018 Mark Jessop <vk5qi@rfhead.net>
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# Released under GNU GPL v3 or later
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#
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import numpy as np
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import os
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# Where to find the samples files.
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# These are all expected to be 96khz float (dtype='c8') files.
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SAMPLE_DIR = "./samples"
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# Directory to output generated files
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GENERATED_DIR = "./generated"
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# Range of Eb/N0 SNRs to produce.
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# 10-20 dB seems to be the range where the demodulators fall over.
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EBNO_RANGE = np.arange(5,20.5,0.5)
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# Normalise the samples to +/- 1.0!
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# If we don't do this, bad things can happen later down the track...
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NORMALISE = True
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# List of samples
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# [filename, baud_date, threshold, sample_rate]
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# filename = string, without path
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# baud_rate = integer
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# threshold = threshold for calculating variance. Deterimined by taking 20*np.log10(np.abs(data)) and looking for packets.
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# sample_rate = input file sample rate.
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SAMPLES = [
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['rs41_96k_float.bin', 4800, -20.0, 96000],
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['rs92_96k_float.bin', 4800, -100, 96000], # No threshold set, as signal is continuous.
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['dfm09_96k_float.bin', 2500, -100, 96000], # Weird baud rate. No threshold set, as signal is continuous.
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['m10_96k_float.bin', 9616, -10.0, 96000], # Really weird baud rate.
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['imet4_96k_float.bin', 1200, -10.0, 96000], # 1200 baud, but AFSK, so we expect 7-8 dB worse performance than the other sondes.
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['imet54_96k_float.bin', 4800, -10.0, 96000], # 4800 baud GMSK
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['rsngp_96k_float.bin', 2400, -100.0, 96000], # RS92-NGP - wider bandwidth.
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['lms6-400_96k_float.bin', 4800, -100, 96000], # LMS6, 400 MHz variant. Continuous signal.
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['mrz_96k_float.bin', 2400, -100, 96000] # MRZ Continuous signal.
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]
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def load_sample(filename):
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_filename = os.path.join(SAMPLE_DIR, filename)
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return np.fromfile(_filename, dtype='c8')
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def save_sample(data, filename):
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_filename = os.path.join(GENERATED_DIR, filename)
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# We have to make sure to convert to complex64..
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data.astype(dtype='c8').tofile(_filename)
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# TODO: Allow saving as complex s16 - see view solution here: https://stackoverflow.com/questions/47086134/how-to-convert-a-numpy-complex-array-to-a-two-element-float-array
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def calculate_variance(data, threshold=-100.0):
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# Calculate the variance of a set of radiosonde samples.
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# Optionally use a threshold to limit the sample the variance
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# is calculated over to ones that actually have sonde packets in them.
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_data_log = 20*np.log10(np.abs(data))
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return np.var(data[_data_log>threshold])
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def add_noise(data, variance, baud_rate, ebno, fs=96000, bitspersymbol=1.0):
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# Add calibrated noise to a sample.
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# Calculate Eb/No in linear units.
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_ebno = 10.0**((ebno)/10.0)
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# Calculate the noise variance we need to add
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_noise_variance = variance*fs/(baud_rate*_ebno*bitspersymbol)
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# Generate complex random samples
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_rand_i = np.sqrt(_noise_variance/2.0)*np.random.randn(len(data))
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_rand_q = np.sqrt(_noise_variance/2.0)*np.random.randn(len(data))
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_noisy = (data + (_rand_i + 1j*_rand_q))
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if NORMALISE:
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print("Normalised to 1.0")
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return _noisy/np.max(np.abs(_noisy))
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else:
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return _noisy
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if __name__ == '__main__':
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for _sample in SAMPLES:
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# Extract the stuff we need from the entry.
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_source = _sample[0]
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_baud_rate = _sample[1]
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_threshold = _sample[2]
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_fs = _sample[3]
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print("Generating samples for: %s" % _source)
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# Read in source file.
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_data = load_sample(_source)
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# Calculate variance
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_var = calculate_variance(_data, _threshold)
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print("Calculated Variance: %.5f" % _var)
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# Now loop through the ebno's and generate the output.
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for ebno in EBNO_RANGE:
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_data_noise = add_noise(_data, variance=_var, baud_rate=_baud_rate, ebno=ebno, fs=_fs)
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_out_file = _source.split('.bin')[0] + "_%04.1fdB"%ebno + ".bin"
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save_sample(_data_noise, _out_file)
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print("Saved file: %s" % _out_file)
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