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acquire-galileo-e5bq.py
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acquire-galileo-e5bq.py
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#!/usr/bin/env python
import optparse
import numpy as np
import scipy.signal
import scipy.fftpack as fft
import gnsstools.galileo.e5bq as e5bq
import gnsstools.nco as nco
import gnsstools.io as io
import gnsstools.util as util
#
# Acquisition search
#
def search(x,prn,doppler_search,ms):
fs = 3*10230000.0
n = 3*10230 # 1 ms coherent integration
doppler_min, doppler_max, doppler_incr = doppler_search
incr = float(e5bq.code_length)/n
c = e5bq.code(prn,0,0,incr,n) # obtain samples of the E5b-Q code
c = fft.fft(np.concatenate((c,np.zeros(n))))
m_metric,m_code,m_doppler = 0,0,0
for doppler in np.arange(doppler_min,doppler_max,doppler_incr): # doppler bins
q = np.zeros(2*n)
w = nco.nco(-doppler/fs,0,2*n)
for block in range(ms): # incoherent sums
b = x[(block*n):((block+2)*n)]
b = b*w
r = fft.ifft(c*np.conj(fft.fft(b)))
q = q + np.absolute(r)
idx = np.argmax(q)
if q[idx]>m_metric:
m_metric = q[idx]
m_code = e5bq.code_length*(float(idx)/n)
m_doppler = doppler
m_code = m_code%e5bq.code_length
return m_metric,m_code,m_doppler
#
# main program
#
parser = optparse.OptionParser(usage="""acquire-galileo-e5bq.py [options] input_filename sample_rate carrier_offset
Acquire Galileo E5bq signals
Examples:
Acquire all Galileo PRNs using standard input with sample rate 69.984 MHz and carrier offset 15.498375 MHz:
acquire-galileo-e5bq.py /dev/stdin 69984000 15498375
Arguments:
input_filename input data file, i/q interleaved, 8 bit signed
sample_rate sampling rate in Hz
carrier_offset offset to E5b carrier in Hz (positive or negative)""")
parser.disable_interspersed_args()
parser.add_option("--prn", default="1-50", help="PRNs to search, e.g. 1,3,7-14,31 (default %default)")
parser.add_option("--doppler-search", metavar="MIN,MAX,INCR", default="-9000,9000,200", help="Doppler search grid: min,max,increment (default %default)")
parser.add_option("--time", type="int", default=80, help="integration time in milliseconds (default %default)")
(options, args) = parser.parse_args()
filename = args[0]
fs = float(args[1])
coffset = float(args[2])
prns = util.parse_list_ranges(options.prn)
doppler_search = util.parse_list_floats(options.doppler_search)
ms = options.time
# read first portion of file
ms_pad = ms + 5
n = int(fs*0.001*ms_pad)
fp = open(filename,"rb")
x = io.get_samples_complex(fp,n)
# resample to 3*10.230 MHz
fsr = 3*10230000.0/fs
nco.mix(x,-coffset/fs,0)
h = scipy.signal.firwin(161,12e6/(fs/2),window='hanning')
x = scipy.signal.filtfilt(h,[1],x)
xr = np.interp((1/fsr)*np.arange(ms_pad*3*10230),np.arange(len(x)),np.real(x))
xi = np.interp((1/fsr)*np.arange(ms_pad*3*10230),np.arange(len(x)),np.imag(x))
x = xr+(1j)*xi
# iterate (in parallel) over PRNs of interest
def worker(p):
x,prn = p
metric,code,doppler = search(x,prn,doppler_search,ms)
return 'prn %2d doppler % 7.1f metric % 7.1f code_offset %6.1f' % (prn,doppler,metric,code)
import multiprocessing as mp
cpus = mp.cpu_count()
results = mp.Pool(cpus).map(worker, map(lambda prn: (x,prn),prns))
for r in results:
print(r)