def indeptest(dim):
R1 = music.covar(s1)
R2 = music.covar(s2)
s1spec = music.Estimator(ants, R1, nsignals=1).spectrum(dim)
s2spec = music.Estimator(ants, R2, nsignals=1).spectrum(dim)
bothspec = music.Estimator(ants, R, nsignals=2).spectrum(dim)
scipy.misc.imsave("s1spec.png", s1spec / s1spec.max())
scipy.misc.imsave("s2spec.png", s2spec / s2spec.max())
scipy.misc.imsave("bothspec.png", bothspec / bothspec.max())
def indeptest(dim):
R1 = music.covar(s1)
R2 = music.covar(s2)
s1spec = music.Estimator(ants,R1,nsignals=1).spectrum(dim)
s2spec = music.Estimator(ants,R2,nsignals=1).spectrum(dim)
bothspec = music.Estimator(ants,R,nsignals=2).spectrum(dim)
sp.misc.imsave("s1spec.png",s1spec/s1spec.max())
sp.misc.imsave("s2spec.png",s2spec/s2spec.max())
sp.misc.imsave("bothspec.png",bothspec/bothspec.max())
def sumspectest(dim=512, n=16):
accum = sp.zeros((dim, dim))
for i in range(n):
mys1 = util.makesamples(ants, s1_aoa[0], s1_aoa[1], nsamp)
mys2 = util.makesamples(ants, s2_aoa[0], s2_aoa[1], nsamp)
mysamples = mys2 + mys1
mysamples = util.awgn(mysamples, snr)
cov = music.covar(mysamples)
accum += music.Estimator(ants, cov, nsignals=2).spectrum((dim, dim))
scipy.misc.imsave("accumspec.png", accum / accum.max())
def sumspectest(dim=512,n=16):
accum = sp.zeros((dim,dim))
for i in range(n):
mys1 = util.makesamples(ants,s1_aoa[0],s1_aoa[1],nsamp)
mys2 = util.makesamples(ants,s2_aoa[0],s2_aoa[1],nsamp)
mysamples = mys2 + mys1
mysamples = util.awgn(mysamples,snr)
cov = music.covar(mysamples)
accum += music.Estimator(ants,cov,nsignals=2).spectrum((dim,dim))
sp.misc.imsave("accumspec.png",accum/accum.max())
def doatest():
print("s1 is {}".format(s1_aoa))
print("s2 is {}".format(s2_aoa))
s1_est = music.Estimator(ants,music.covar(s1),nsignals=1)
s2_est = music.Estimator(ants,music.covar(s2),nsignals=1)
# s1
t1 = time()
s1_res = s1_est.doasearch()[0]
t1 = time() - t1
s1_err = sp.rad2deg(util.aoa_diff_rad(s1_res,s1_aoa))
print("s1: found {} in {}s, error {} deg".format(s1_res,t1,s1_err))
# s2
t2 = time()
s2_res = s2_est.doasearch()[0]
t2 = time() - t2
s2_err = sp.rad2deg(util.aoa_diff_rad(s2_res,s2_aoa))
print("s2: found {} in {}s, error {} deg".format(s2_res,t2,s2_err))
# both signals
bothres = est.doasearch()
print("Both signals:\n{}".format(bothres))
s2_aoa_deg = [120, 0]
s1_aoa = (sp.deg2rad(s1_aoa_deg[0]), sp.deg2rad(s1_aoa_deg[1]))
#s2_aoa = (pi/2 + sp.randn()/2, sp.randn()/2)
s2_aoa = (sp.deg2rad(s2_aoa_deg[0]), sp.deg2rad(s2_aoa_deg[1]))
s1 = util.makesamples(ants, s1_aoa[0], s1_aoa[1], nsamp)
s2 = util.makesamples(ants, s2_aoa[0], s2_aoa[1], nsamp)
samples = s2 + s1
samples = util.awgn(samples, snr)
# add noise to s1 and s2
s1 = util.awgn(s1, snr)
s2 = util.awgn(s2, snr)
R = music.covar(samples)
est = music.Estimator(ants, R, nsignals=2)
def spectest(n=256):
t = time()
spec = est.spectrum((n, n))
elapsed = time() - t
print("spectrum calculation time: {}".format(elapsed))
return spec
def sumspectest(dim=512, n=16):
accum = sp.zeros((dim, dim))
for i in range(n):
mys1 = util.makesamples(ants, s1_aoa[0], s1_aoa[1], nsamp)
snr = -6
s1_aoa = (pi/2,0)
#s2_aoa = (pi/2 + sp.randn()/2, sp.randn()/2)
s2_aoa = (pi/2+pi/6, -pi/6)
s1 = util.makesamples(ants,s1_aoa[0],s1_aoa[1],nsamp)
s2 = util.makesamples(ants,s2_aoa[0],s2_aoa[1],nsamp)
samples = s2 + s1
samples = util.awgn(samples,snr)
# add noise to s1 and s2
s1 = util.awgn(s1,snr)
s2 = util.awgn(s2,snr)
R = music.covar(samples)
est = music.Estimator(ants,R,nsignals=2)
def spectest(n=256):
t = time()
spec = est.spectrum((n,n))
elapsed = time() - t
print("spectrum calculation time: {}".format(elapsed))
return spec
def sumspectest(dim=512,n=16):
accum = sp.zeros((dim,dim))
for i in range(n):
mys1 = util.makesamples(ants,s1_aoa[0],s1_aoa[1],nsamp)
mys2 = util.makesamples(ants,s2_aoa[0],s2_aoa[1],nsamp)
mysamples = mys2 + mys1
