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Merge pull request #21 from aerospaceresearch/Vinay_dev
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Vinay dev
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7andahalf authored Jul 27, 2018
2 parents d741eef + 4ae0972 commit 0929526
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265 changes: 265 additions & 0 deletions directdemod/decode_funcube.py
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'''
Funcube
'''
from directdemod import source, sink, chunker, comm, constants, filters
import numpy as np
import logging
import scipy.signal as signal
#import matplotlib.pylab as plt
import math, time

## Inspired from: https://github.com/dbdexter-dev/meteor_demod
# Thank you!

################# OBJECTS

class agc():
def __init__(self):
self.mean = 180.0
self.dc = 0.0

def adjust(self, inp):

# moving avg to get dc
self.dc = ((self.dc * ((1024*1024)-1)*1.0) + inp) / (1024*1024*1.0)
inp -= self.dc

# moving avg of amplitude
self.mean = (self.mean * 1.0 * (65536.0 - 1) + ((np.real(inp)*np.real(inp) + np.imag(inp)*np.imag(inp))**0.5)) / 65536.0

# multiply the input value
if 180.0 / self.mean > 20:
return inp * 20
else:
return inp * 180.0 / self.mean

class costas():

def __init__(self):
self.freq = 0.001
self.phase = 0.00
self.output = np.exp(-1j*self.phase)

self.damping = 0.70710678118
self.bw = 0.05235833333
self.compAlphaBeta(self.damping, self.bw)

self.mean = 1.0
self.plllock = False

self.hypstore = []
for i in range(256):
self.hypstore.append(np.tanh(i-128))

def compAlphaBeta(self, damping, bw):
denom = (1.0 + 2.0*damping*bw + bw*bw)
self.alpha = (4*damping*bw)/denom
self.beta = (4*bw*bw)/denom

def loop(self, samp):
self.output = np.exp(-1j*self.phase)

correctedIn = samp * self.output

error = np.imag(correctedIn) * self.hyp(np.real(correctedIn))/255.0
self.mean = (self.mean * (39999.0) + np.abs(error))/40000.0
if error > 1:
error = 1.0
elif (error < -1):
error = -1.0

self.phase = math.fmod(self.phase + self.freq + self.alpha*error, 2*np.pi)
self.freq = self.freq + self.beta*error

if not self.plllock and self.mean < 0.2:
self.compAlphaBeta(self.damping, self.bw/2.0)
self.plllock = True
elif self.plllock and self.mean > 0.5:
self.compAlphaBeta(self.damping, self.bw)
self.plllock = False
return correctedIn

def hyp(self, x):
if x > 127: return 1
if x < -128: return -1
return self.hypstore[int(x+128)]

def lim(x):
if x < -128.0:
return -128
if x > 127.0:
return 127
if x > 0 and x < 1:
return 1
if x > -1 and x < 0:
return -1
return int(x)

def limBin(x):
if x <= 0:
return 0
else:
return 1


'''
Object to Funcube
'''

class decode_funcube:

'''
Object to decode Funcube
'''

def __init__(self, sigsrc, offset, bw):

'''Initialize the object
Args:
sigsrc (:obj:`commSignal`): IQ data source
offset (:obj:`float`): Frequency offset of source in Hz
bw (:obj:`int`, optional): Bandwidth
'''

self.__bw = bw
if self.__bw is None:
self.__bw = 7000
self.__sigsrc = sigsrc
self.__offset = offset
self.__useful = 0

@property
def useful(self):

'''See if signal was found
Returns:
:obj:`int`: 0 if not found, 1 if found
'''

return self.__useful

@property
def getSyncs(self):

'''Get syncs of Funcube
Returns:
:obj:`list`: list of detected syncs
'''

# create chunker object
chunkerObj = chunker.chunker(self.__sigsrc)

# butter filter
bf = filters.butter(self.__sigsrc.sampFreq, self.__bw)

# init vars for gardner
symbolPeriod = self.__sigsrc.sampFreq/12000
timing = 0.00
gardnerC, gardnerB, gardnerA = 0.00, 0.00, 0.00
agcObj = agc()
pllObj = costas()
ctr = 0

sync = np.array([int(i) for i in "101000110001000000000001010111100"])

sync12khz = np.repeat(sync, 10)

sync[sync == 1] = 127
sync[sync == 0] = -128
sync2mhz = np.repeat(sync, int(2048000/1200))

maxResBuff = []
minResBuff = []
maxBuffRetain = -1
maxBuffStart = 0

minSyncs = []
maxSyncs = []

numCtrs = int(chunkerObj.getChunks[-1][-1]*12000/2048000)
start_time = time.time()
lastMin = None
ctrMain = 0
for i in chunkerObj.getChunks[:]:

#interpolate
sig = comm.commSignal(self.__sigsrc.sampFreq, self.__sigsrc.read(*i))
sig.offsetFreq(self.__offset)
sig.filter(bf)

# main loop
for i in sig.signal:

### MAXSYNC detection by correlation

# start storing 2mhz values near sync possible regions
if not lastMin is None and (ctr > lastMin + (4.9*12000) - (2*len(sync12khz)) or not maxBuffRetain == -1):
if len(maxResBuff) == 0:
maxBuffStart = ctrMain
maxResBuff.append(lim(np.real(i*pllObj.output)/2))

# see if correlation is to be performed
if maxBuffRetain == -1:
if len(maxResBuff) > (2 * len(sync2mhz)):
maxBuffStart += 1
maxResBuff.pop(0)
elif maxBuffRetain == 0:
maxBuffRetain -= 1
corr = np.abs(np.correlate(maxResBuff,sync2mhz, mode='same'))
logging.info("MAXSYNC %d", maxBuffStart+np.argmax(corr))
#print("MAXSYNC", maxBuffStart, np.argmax(corr), maxBuffStart+np.argmax(corr))
maxSyncs.append(maxBuffStart+np.argmax(corr))
maxResBuff = []

#plt.plot(corr)
#plt.show()
else:
maxBuffRetain -= 1

# Gardners algorithm
if timing >= symbolPeriod/2 and timing < ((symbolPeriod/2)+1):
gardnerB = agcObj.adjust(i)

elif timing >= symbolPeriod:
gardnerA = agcObj.adjust(i)
timing -= symbolPeriod
resync_error = (np.imag(gardnerA) - np.imag(gardnerC)) * np.imag(gardnerB)
timing += (resync_error*symbolPeriod/(2000000.0))
gardnerC = gardnerA
gardnerA = pllObj.loop(gardnerA)
ctr += 1

# 12khz buffer
minResBuff.append(limBin(np.real(gardnerA)))
minResBuff = minResBuff[-1*len(sync12khz):]

# print periodic status
try:
if ctr%1000 == 0:
logging.info("[%.2f percent complete] [%.2f seconds elapsed] [%.2f seconds remain]", (ctr*100/numCtrs), (time.time() - start_time), (((time.time() - start_time)/(ctr/numCtrs))-(time.time() - start_time)))
#print(ctr, '[%.2f' %(ctr*100/numCtrs),"%]",'[%.2f' %(time.time() - start_time),"seconds elapsed]",'[%.2f' %(((time.time() - start_time)/(ctr/numCtrs))-(time.time() - start_time)), "seconds remaining]", pllObj.mean)
except:
pass

# see if sync is present
if len(minResBuff) == len(sync12khz) and np.abs(np.sum(np.abs(np.array(minResBuff) - sync12khz)) - (len(sync12khz)/2)) > 120:
logging.info("MINSYNC: %d %f",ctr, np.abs(np.sum(np.abs(np.array(minResBuff) - sync12khz)) - (len(sync12khz)/2)))
#print("MINSYNC:",ctr, np.abs(np.sum(np.abs(np.array(minResBuff) - sync12khz)) - (len(sync12khz)/2)))
minSyncs.append(ctr)
lastMin = ctr
maxBuffRetain = 2 * len(sync2mhz)

timing += 1
ctrMain += 1

if len(maxSyncs) > 0:
# check usefulness
if np.min(np.abs(np.diff(maxSyncs) - (4.98*2048000))) < (0.2*2048000):
self.__useful = 1
return list(maxSyncs)[1:]
else:
return []

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