def test_scaled_weights():
for n in range(1,5):
for alpha in np.linspace(0.99, 1.01, 100):
for beta in range(0,2):
for kappa in range(0,2):
Wm, Wc = SUKF.weights(n, alpha, 0, 3-n)
assert abs(sum(Wm) - 1) < 1.e-1
assert abs(sum(Wc) - 1) < 1.e-1
def test_scaled_weights():
for n in range(1, 5):
for alpha in np.linspace(0.99, 1.01, 100):
for beta in range(0, 2):
for kappa in range(0, 2):
Wm, Wc = SUKF.weights(n, alpha, 0, 3 - n)
assert abs(sum(Wm) - 1) < 1.e-1
assert abs(sum(Wc) - 1) < 1.e-1
from filterpy.kalman import UnscentedKalmanFilter as UKF
from filterpy.kalman import ScaledUnscentedKalmanFilter as SUKF
from filterpy.common import Q_discrete_white_noise
""" This is an example of the bearing only problem. You have a platform,
usually a ship, that can only get the bearing to a moving target. Assuming
platform is stationary, this is a very difficult problem because there are
an infinite number of solutions. The literature is filled with this example,
along with proposed solutions (usually, platform makes manuevers).
"""
dt = 0.1
y = 20
platform_pos = (0, 20)
sf = SUKF(2, 1, dt, alpha=1.e-4, beta=2., kappa=1.)
sf.Q = Q_discrete_white_noise(2, dt, .1)
f = UKF(2, 1, dt, kappa=0.)
f.Q = Q_discrete_white_noise(2, dt, .1)
def fx(x, dt):
""" state transition function"""
# pos = pos + vel
# vel = vel
return array([x[0] + x[1], x[1]])
def hx(x):
from filterpy.common import Q_discrete_white_noise
""" This is an example of the bearing only problem. You have a platform,
usually a ship, that can only get the bearing to a moving target. Assuming
platform is stationary, this is a very difficult problem because there are
an infinite number of solutions. The literature is filled with this example,
along with proposed solutions (usually, platform makes manuevers).
"""
dt = 0.1
y = 20
platform_pos = (0, 20)
sf = SUKF(2, 1, dt, alpha=1.0e-4, beta=2.0, kappa=1.0)
sf.Q = Q_discrete_white_noise(2, dt, 0.1)
f = UKF(2, 1, dt, kappa=0.0)
f.Q = Q_discrete_white_noise(2, dt, 0.1)
def fx(x, dt):
""" state transition function"""
# pos = pos + vel
# vel = vel
return array([x[0] + x[1], x[1]])
