Last active
August 29, 2015 22:47
-
-
Save connerbrooks/ab8d05fdd7cb3f53bf6a to your computer and use it in GitHub Desktop.
1D Kalman Filter
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# Write a program that will iteratively update and | |
# predict based on the location measurements | |
# and inferred motions shown below. | |
def update(mean1, var1, mean2, var2): | |
new_mean = float(var2 * mean1 + var1 * mean2) / (var1 + var2) | |
new_var = 1./(1./var1 + 1./var2) | |
return [new_mean, new_var] | |
def predict(mean1, var1, mean2, var2): | |
new_mean = mean1 + mean2 | |
new_var = var1 + var2 | |
return [new_mean, new_var] | |
measurements = [5., 6., 7., 9., 10.] | |
motion = [1., 1., 2., 1., 1.] | |
measurement_sig = 4. | |
motion_sig = 2. | |
mu = 0. | |
sig = 10000. | |
for i in range(len(motion)): | |
[mu, sig] = update(mu, sig, measurements[i], measurement_sig) | |
print [mu, sig] | |
[mu, sig] = predict(mu, sig, motion[i], motion_sig) | |
print [mu, sig] | |
print [mu, sig] |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment