Reputation: 1006
I try to implement Kalman filter for predicting speed one step ahead. Implementing in python H=np.diag([1,1]) H
Result: array([[1, 0], [0, 1]]) For measurement vector datafile is csv file containing time as one column and speed in another column
measurements=np.vstack((mx,my,datafile.speed))
#length of meassurement
m=measurements.shape[1]
print(measurements.shape)
Output: (3, 1069)
for filterstep in range(m-1):
#Time Update
#=============================
#Project the state ahead
x=A*x
#Project the error covariance ahead
P=A*P*A.T+Q
#Measurement Update(correction)
#===================================
#if there is GPS measurement
if GPS[filterstep]:
#COmpute the Kalman Gain
S =(H*P*H).T + R
S_inv=S.inv()
K=(P*H.T)*S_inv
#Update the estimate via z
Z = measurements[:,filterstep].reshape(H.shape[0],1)
y=Z-(H*x)
x = x + (K*y)
#Update the error covariance
P=(I-(K*H))*P
# Save states for Plotting
x0.append(float(x[0]))
x1.append(float(x[1]))
Zx.append(float(Z[0]))
Zy.append(float(Z[1]))
Px.append(float(P[0,0]))
Py.append(float(P[1,1]))
Kx.append(float(K[0,0]))
Ky.append(float(K[1,0]))
Error comes as:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-80-9b15fccbaca8> in <module>()
20
21 #Update the estimate via z
---> 22 Z = measurements[:,filterstep].reshape(H.shape[0],1)
23 y=Z-(H*x)
24 x = x + (K*y)
ValueError: total size of new array must be unchanged
How can i remove such error
Upvotes: 0
Views: 1415
Reputation: 655
This line is incorrect:
S =(H*P*H).T + R
The correct code is:
S =(H*P*H.T) + R
I'm having trouble following what the measurements are. You stated " array([[1, 0], [0, 1]]) For measurement vector datafile is csv file containing time as one column and speed in another column"
So that reads to me as a CSV file with two columns, one time, and one speed. In that case you have only one measurement at each time, the speed. For a single measurement, your H-matrix should be a row-vector.
Upvotes: 1