def analyze(P: dict):
tx = loadbin(P['txfn'], P['txfs'], tlim=(0, P['tm']))
if P['verbose']:
plotraw(tx, None, P['txfs'])
print(
f'Using {P["pri"]*1000} ms PRI for {P["tm"]*1e6} us chirp, with {P["Nchirp"]} pulses incoherently integrated'
)
# %%
NrxPRI = int(P['pri'] * rxfs) # samples in a PRI
Lrx = NrxPRI * P['Nchirp']
if P['rxfn'] is not None:
Nsampfile = P['rxfn'].stat().st_size // LSAMP
Tfile = Nsampfile / P['rxfs']
print(P['rxfn'], f'is {Tfile:0.1f} seconds long')
isamp = range(0, Nsampfile, Lrx)
else:
print('simulation')
isamp = range(0, Nsim * Lrx, Lrx)
t = np.array(isamp) / P['txfs'] # elapsed time seconds
if P['t0'] is not None:
t += P['t0']
# %%
if P['outfn']:
print('writing', outfn)
with h5py.File(outfn, 'w') as f:
f.create_dataset('Rxy',
shape=(t.size, int(NrxPRI * P['resample'])),
dtype=np.complex128,
chunks=True,
compression='gzip')
f['t'] = t
f['lags'] = np.arange(-NrxPRI // 2, NrxPRI // 2)
f['t0'] = P['t0']
f['cmd'] = ' '.join(sys.argv)
f['fs'] = P['txfs']
for k, (i, j) in enumerate(zip(isamp, isamp[1:])):
if P['rxfn'] is None:
rx = 0.05 * tx + 0.1 * tx.max() * (
np.random.randn(P['Nchirp'], tx.size) +
1j * np.random.randn(P['Nchirp'], tx.size))
rx = rx.ravel()
else:
rx = loadbin(P['rxfn'], P['rxfs'], tlim=P['t0'], isamp=(i, j))
lags = procchunk(rx, tx, P)
if outfn:
with h5py.File(outfn, 'a') as f:
f['Rxy'][k, :] = lags
print(
f'processing t={t[k]:.2f} sec., {t[k]/Tfile*100:.3f} % complete.\r',
end="")
def analyze(P: dict):
tx = loadbin(P["txfn"], P["txfs"], tlim=(0, P["tm"]))
if P["verbose"]:
plotraw(tx, None, P["txfs"])
print(
f'Using {P["pri"]*1000} ms PRI for {P["tm"]*1e6} us chirp, with {P["Nchirp"]} pulses incoherently integrated'
)
# %%
NrxPRI = int(P["pri"] * rxfs) # samples in a PRI
Lrx = NrxPRI * P["Nchirp"]
if P["rxfn"] is not None:
Nsampfile = P["rxfn"].stat().st_size // LSAMP
Tfile = Nsampfile / P["rxfs"]
print(P["rxfn"], f"is {Tfile:0.1f} seconds long")
isamp = range(0, Nsampfile, Lrx)
else:
print("simulation")
isamp = range(0, Nsim * Lrx, Lrx)
t = np.array(isamp) / P["txfs"] # elapsed time seconds
if P["t0"] is not None:
t += P["t0"]
# %%
if P["outfn"]:
print("writing", outfn)
with h5py.File(outfn, "w") as f:
f.create_dataset(
"Rxy",
shape=(t.size, int(NrxPRI * P["resample"])),
dtype=np.complex128,
chunks=True,
compression="gzip",
)
f["t"] = t
f["lags"] = np.arange(-NrxPRI // 2, NrxPRI // 2)
f["t0"] = P["t0"]
f["cmd"] = " ".join(sys.argv)
f["fs"] = P["txfs"]
for k, (i, j) in enumerate(zip(isamp, isamp[1:])):
if P["rxfn"] is None:
rx = 0.05 * tx + 0.1 * tx.max() * (
np.random.randn(P["Nchirp"], tx.size) +
1j * np.random.randn(P["Nchirp"], tx.size))
rx = rx.ravel()
else:
rx = loadbin(P["rxfn"], P["rxfs"], tlim=P["t0"], isamp=(i, j))
lags = procchunk(rx, tx, P)
if outfn:
with h5py.File(outfn, "a") as f:
f["Rxy"][k, :] = lags
print(
f"processing t={t[k]:.2f} sec., {t[k]/Tfile*100:.3f} % complete.\r",
end="")
def analyze(P:dict):
tx = loadbin(P['txfn'], P['txfs'], tlim=(0,P['tm']))
if P['verbose']:
plotraw(tx, None, P['txfs'])
print(f'Using {P["pri"]*1000} ms PRI for {P["tm"]*1e6} us chirp, with {P["Nchirp"]} pulses incoherently integrated')
# %%
NrxPRI = int(P['pri']*rxfs) # samples in a PRI
Lrx = NrxPRI*P['Nchirp']
if P['rxfn'] is not None:
Nsampfile = P['rxfn'].stat().st_size//LSAMP
Tfile = Nsampfile / P['rxfs']
print(P['rxfn'], f'is {Tfile:0.1f} seconds long')
isamp = range(0, Nsampfile, Lrx)
else:
print('simulation')
isamp = range(0, Nsim*Lrx, Lrx)
t = np.array(isamp) / P['txfs'] # elapsed time seconds
if P['t0'] is not None:
t += P['t0']
# %%
if P['outfn']:
print('writing',outfn)
with h5py.File(outfn,'w') as f:
f.create_dataset('Rxy',shape=(t.size, int(NrxPRI*P['resample'])),
dtype=np.complex128,chunks=True,compression='gzip')
f['t'] = t
f['lags'] = np.arange(-NrxPRI//2,NrxPRI//2)
f['t0'] = P['t0']
f['cmd'] = ' '.join(sys.argv)
f['fs'] = P['txfs']
for k,(i,j) in enumerate(zip(isamp,isamp[1:])):
if P['rxfn'] is None:
rx = 0.05*tx + 0.1*tx.max()*(np.random.randn(P['Nchirp'],tx.size)
+ 1j*np.random.randn(P['Nchirp'],tx.size))
rx = rx.ravel()
else:
rx = loadbin(P['rxfn'], P['rxfs'], tlim=P['t0'], isamp=(i, j))
lags = procchunk(rx, tx, P)
if outfn:
with h5py.File(outfn,'a') as f:
f['Rxy'][k,:] = lags
print(f'processing t={t[k]:.2f} sec., {t[k]/Tfile*100:.3f} % complete.\r',end="")
def cwproc(fn, fsaudio, tlim, fc, ax=None):
fn = Path(p.fn).expanduser()
fs = int(p.fs) # to allow 100e3 on command line
fsaudio = int(fsaudio)
dat, t = loadbin(fn, fs, tlim)
dat = freq_translate(dat, fc, fs)
dat = downsample(dat, fs, fsaudio)
# %% play sound
if 0: # not for when looping, it will try to play dozens of files at once.
playaudio(dat, fsaudio, p.outwav)
#%% plots
if 0 and dat.size < 500e3: # plots will crash if too many points
if ax is None:
ax = figure().gca()
ax.plot(t + tlim[0], dat.real[:])
ax.set_title(f"{fn.name} Fs: {fs} Hz t={tlim[0]}..{tlim[1]}")
ax.set_xlabel("time [sec]")
ax.set_ylabel("amplitude")
f, tt, Sxx, Sp = spec(dat,
fsaudio,
p.flim,
tlim,
be,
vlim=p.vlim,
zpad=p.zeropad)
# %% analysis
Abin = np.empty(be.size - 1)
for i in range(len(be) - 1):
ibin = (f < be[i + 1]) & (f > be[i])
Abin[i] = Sp[ibin].sum()
return Abin
def cwproc(fn, fsaudio, tlim, fc, ax=None):
fn=Path(p.fn).expanduser()
fs = int(p.fs) # to allow 100e3 on command line
fsaudio = int(fsaudio)
dat,t = loadbin(fn, fs, tlim)
dat = freq_translate(dat,fc,fs)
dat = downsample(dat,fs,fsaudio)
# %% play sound
if 0: # not for when looping, it will try to play dozens of files at once.
playaudio(dat, fsaudio, p.outwav)
#%% plots
if 0 and dat.size < 500e3: # plots will crash if too many points
if ax is None:
ax = figure().gca()
ax.plot(t + tlim[0], dat.real[:])
ax.set_title(f'{fn.name} Fs: {fs} Hz t={tlim[0]}..{tlim[1]}')
ax.set_xlabel('time [sec]')
ax.set_ylabel('amplitude')
f,tt,Sxx,Sp = spec(dat, fsaudio, p.flim, tlim, be, vlim=p.vlim, zpad=p.zeropad)
# %% analysis
Abin = np.empty(be.size-1)
for i in range(len(be)-1):
ibin = (f < be[i+1]) & (f > be[i])
Abin[i] = Sp[ibin].sum()
return Abin
def dodemod(rx, P: dict):
aud = None
fs = P["rxfs"]
if P["demod"] == "chirp":
tx = loadbin(P["txfn"], P["txfs"])
if tx is None:
warnings.warn("simulated chirp reception")
tx = rx
rx = 0.05 * rx + 0.1 * rx.max() * (np.random.randn(rx.size) +
1j * np.random.randn(rx.size))
txfs = fs
else:
rx = scipy.signal.resample_poly(rx, UP, DOWN)
fs = txfs = P["txfs"]
txsec = tx.size / txfs # length of TX in seconds
if P["pri"] is None:
pri = txsec
print(
f'Using {pri*1000} ms PRI and {P["Npulse"]} pulses incoherently integrated'
)
# %% integration
NrxPRI = int(fs * pri) # Number of RX samples per PRI
NrxStack = rx.size // NrxPRI # number of complete PRIs received in this data
Nint = NrxStack // P["Npulse"] # Number of steps we'll take iterating
Nextract = (
P["Npulse"] * NrxPRI
) # total number of samples to extract (in general part of one PRI is discarded after numerous PRIs)
ax = None
for i in range(Nint):
ci = slice(i * Nextract, (i + 1) * Nextract)
rxint = rx[ci].reshape((NrxPRI, P["Npulse"])).mean(axis=1)
Rxy = np.correlate(tx, rxint, "full")
ax = plotxcor(Rxy, txfs, ax)
draw()
pause(0.5)
elif P["demod"] == "am":
aud = am_demod(P["again"] * rx,
fs,
fsaudio,
P["fc"],
p.audiobw,
frumble=p.frumble,
verbose=True)
elif P["demod"] == "ssb":
aud = ssb_demod(P["again"] * rx,
fs,
fsaudio,
P["fc"],
p.audiobw,
verbose=True)
return aud, fs
def main():
p = ArgumentParser()
p.add_argument('fn', help='binary raw IQ capture SDR file to analyze')
p.add_argument('fs', help='sampling frequency [Hz]', type=int)
p.add_argument('-fc', help='baseband tunding freq [Hz]', type=float)
p.add_argument('-t', '--tlim',
help='start stop increment [seconds] to load',
type=float, nargs=2, default=(0., None))
p.add_argument('-v', '--verbose', action='store_true')
P = p.parse_args()
fn = Path(P.fn).expanduser()
assert isinstance(P.fs, (float, int))
fs = int(P.fs)
# %%
sig = loadbin(fn, fs, P.tlim)
# %%
m = fm_demod(sig, fs, fsaudio, P.fc, 75e3, P.verbose)
playaudio(m, fsaudio)
show()
def getrx(P: dict):
rx = loadbin(P["rxfn"], P["rxfs"], P["tlim"])
plotraw(rx, None, P["rxfs"])
return rx
help='subspace method (esprit,rootmusic)',
default='esprit')
p.add_argument('--noest',
help='skip estimation (just plot) for debugging',
action='store_true')
p.add_argument(
'--python',
help='force Python subspace (disable Fortran) for debugging',
action='store_true')
p.add_argument('--all',
help='show all tone freq, including feedthrough',
action='store_true')
p = p.parse_args()
fs = int(p.fs)
if p.fn is None: #simulation
rx, t = cwsim(fs, p.Np, p.T)
else: # load data file
rx = loadbin(p.fn, fs, p.tlim)
rx = freq_translate(rx, p.fx0, fs)
rx = downsample(rx, fs, fsaudio)
#%% estimate beat frequency
if not p.noest:
fb_est, conf = cw_est(rx, fsaudio, p.Nt, p.method, p.python, p.all)
print('estimated beat frequencies', fb_est)
print('sigma', conf)
#%% plot
cwplot(fb_est, rx.squeeze(), t, fsaudio, p.fn)
show()
def getrx(P: dict):
rx = loadbin(P['rxfn'], P['rxfs'], P['tlim'])
plotraw(rx, None, P['rxfs'])
return rx
p = ArgumentParser()
p.add_argument('fn',help='data file .bin to analyze',nargs='?',default=None)
p.add_argument('-fs',help='baseband sampling frequency [Hz]',type=float,default=16e3)
p.add_argument('-Np',help='number of pulses to integrate',type=int,default=1)
p.add_argument('-fx0',help='frequency translation center frequency',type=float)
p.add_argument('-Nt',help='number of tones to find',type=int,default=2)
p.add_argument('-T',help='pulse length (seconds)',type=float,default=0.1)
p.add_argument('-t','--tlim',help='time to analyze e.g. -t 3 4 means process from t=3 to t=4 seconds',nargs=2,type=float )
p.add_argument('-m','--method',help='subspace method (esprit,rootmusic)',default='esprit')
p.add_argument('--noest',help='skip estimation (just plot) for debugging',action='store_true')
p.add_argument('--python',help='force Python subspace (disable Fortran) for debugging',action='store_true')
p.add_argument('--all',help='show all tone freq, including feedthrough',action='store_true')
p = p.parse_args()
fs = int(p.fs)
if p.fn is None: #simulation
rx,t = cwsim(fs, p.Np, p.T)
else: # load data file
rx = loadbin(p.fn, fs, p.tlim)
rx = freq_translate(rx,p.fx0,fs)
rx = downsample(rx, fs, fsaudio)
#%% estimate beat frequency
if not p.noest:
fb_est,conf = cw_est(rx, fsaudio, p.Nt, p.method, p.python, p.all)
print('estimated beat frequencies',fb_est)
print('sigma',conf)
#%% plot
cwplot(fb_est,rx.squeeze(),t, fsaudio, p.fn)
show()