daviddoji/Kalman-and-Bayesian-Filters-in-Python
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Expanded ILS coverage.

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Fixed notation for a priori and a posteriori variables.
Explained how to compute H matrix by linearizing.
This commit is contained in:
Roger Labbe 2015-03-01 11:16:59 -08:00
parent aa7ab29afa
commit 08328f0f0b
2 changed files with 133 additions and 107 deletions
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220
07_Kalman_Filter_Math.ipynb
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20
code/ukf_internal.py
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@ -59,6 +59,24 @@ def show_three_gps():
plt.show()
def show_four_gps():
circle1=plt.Circle((-4,2),5,color='#004080',fill=False,linewidth=20, alpha=.7)
circle2=plt.Circle((5.5,1),5,color='#E24A33', fill=False, linewidth=8, alpha=.7)
circle3=plt.Circle((0,-3),6,color='#534543',fill=False, linewidth=13, alpha=.7)
circle4=plt.Circle((0,8),5,color='#214513',fill=False, linewidth=13, alpha=.7)
fig = plt.gcf()
ax = fig.gca()
ax.add_patch(circle1)
ax.add_patch(circle2)
ax.add_patch(circle3)
ax.add_patch(circle4)
plt.axis('equal')
plt.show()
def show_sigma_transform():
fig = plt.figure()
ax=fig.gca()
@ -174,7 +192,7 @@ def show_sigmas_for_2_kappas():
if __name__ == '__main__':
show_three_gps()
show_four_gps()
#show_sigma_transform()
#show_sigma_selections()