本文整理汇总了Python中filterpy.kalman.UnscentedKalmanFilter.Q[0,0]方法的典型用法代码示例。如果您正苦于以下问题：Python UnscentedKalmanFilter.Q[0,0]方法的具体用法？Python UnscentedKalmanFilter.Q[0,0]怎么用？Python UnscentedKalmanFilter.Q[0,0]使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类filterpy.kalman.UnscentedKalmanFilter的用法示例。
在下文中一共展示了UnscentedKalmanFilter.Q[0,0]方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_circle
# 需要导入模块: from filterpy.kalman import UnscentedKalmanFilter [as 别名]
# 或者: from filterpy.kalman.UnscentedKalmanFilter import Q[0,0] [as 别名]
def test_circle():
from filterpy.kalman import KalmanFilter
from math import radians
def hx(x):
radius = x[0]
angle = x[1]
x = cos(radians(angle)) * radius
y = sin(radians(angle)) * radius
return np.array([x, y])
def fx(x, dt):
return np.array([x[0], x[1]+x[2], x[2]])
std_noise = .1
f = UKF(dim_x=3, dim_z=2, dt=.01, hx=hx, fx=fx, kappa=0)
f.x = np.array([50., 90., 0])
f.P *= 100
f.R = np.eye(2)*(std_noise**2)
f.Q = np.eye(3)*.001
f.Q[0,0]=0
f.Q[2,2]=0
kf = KalmanFilter(dim_x=6, dim_z=2)
kf.x = np.array([50., 0., 0, 0, .0, 0.])
F = np.array([[1., 1., .5, 0., 0., 0.],
[0., 1., 1., 0., 0., 0.],
[0., 0., 1., 0., 0., 0.],
[0., 0., 0., 1., 1., .5],
[0., 0., 0., 0., 1., 1.],
[0., 0., 0., 0., 0., 1.]])
kf.F = F
kf.P*= 100
kf.H = np.array([[1,0,0,0,0,0],
[0,0,0,1,0,0]])
kf.R = f.R
kf.Q[0:3, 0:3] = Q_discrete_white_noise(3, 1., .00001)
kf.Q[3:6, 3:6] = Q_discrete_white_noise(3, 1., .00001)
measurements = []
results = []
zs = []
kfxs = []
for t in range (0,12000):
a = t / 30 + 90
x = cos(radians(a)) * 50.+ randn() * std_noise
y = sin(radians(a)) * 50. + randn() * std_noise
# create measurement = t plus white noise
z = np.array([x,y])
zs.append(z)
f.predict()
f.update(z)
kf.predict()
kf.update(z)
# save data
results.append (hx(f.x))
kfxs.append(kf.x)
#print(f.x)
results = np.asarray(results)
zs = np.asarray(zs)
kfxs = np.asarray(kfxs)
print(results)
if DO_PLOT:
plt.plot(zs[:,0], zs[:,1], c='r', label='z')
plt.plot(results[:,0], results[:,1], c='k', label='UKF')
plt.plot(kfxs[:,0], kfxs[:,3], c='g', label='KF')
plt.legend(loc='best')
plt.axis('equal')