Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fix documentation and covariance calculation for Constant Turn Transition Models #1000

Merged
merged 3 commits into from
Apr 30, 2024
Merged

Fix documentation and covariance calculation for Constant Turn Transition Models #1000

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
d160360
Align documentation of KnownTurnRate with the code definition of cova…
csherman-dstl Apr 29, 2024
c765e02
Change Documentation and covariance calculation for Constant Turn Model.
csherman-dstl Apr 29, 2024
4b0a87d
Change results of test_diekf to reflect the change in covariance calc…
csherman-dstl Apr 29, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
8 changes: 4 additions & 4 deletions stonesoup/models/transition/linear.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -703,14 +703,14 @@ class KnownTurnRate(KnownTurnRateSandwich):

.. math::
Q_t & = & \begin{bmatrix}
q_x^2 \frac{dt^3}{3} & q_x^2 \frac{dt^2}{2} &
q_x \frac{dt^3}{3} & q_x \frac{dt^2}{2} &
0 & 0 \\
q_x^2 \frac{dt^2}{2} & q_x^2 dt &
q_x \frac{dt^2}{2} & q_x dt &
0 & 0 \\
0 & 0 &
q_y^2 \frac{dt^3}{3} & q_y^2 \frac{dt^2}{2}\\
q_y \frac{dt^3}{3} & q_y \frac{dt^2}{2}\\
0 & 0 &
q_y^2 \frac{dt^2}{2} & q_y^2 dt
q_y \frac{dt^2}{2} & q_y dt
\end{bmatrix}
"""

Expand Down
26 changes: 13 additions & 13 deletions stonesoup/models/transition/nonlinear.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -56,22 +56,22 @@ class ConstantTurn(GaussianTransitionModel, TimeVariantModel):

.. math::
F(x) & = & \begin{bmatrix}
x+ \frac{x_{vel}}{\omega}\sin\omega dt -
\frac{y_{vel}}{\omega}(1-\cos\omega dt) \\
x_{vel}\cos\omega dt - y_{vel}\sin\omega dt \\
y+ \frac{v_{vel}}{\omega}\sin\omega dt +
\frac{x_{vel}}{\omega}(1-\cos\omega dt) \\
x_{vel}\sin\omega dt + y_{vel}\sin\omega dt \\
\omega
1 & \frac{\sin\omega dt}{\omega} & 0 & -
\frac{(1-\cos\omega dt)}{\omega} & 0 \\
0 & \cos\omega dt & 0 & - \sin\omega dt & 0 \\
0 & \frac{(1-\cos\omega dt)}{\omega} & 1 &
\frac{\sin\omega dt}{\omega} & 0 \\
0 & \sin\omega dt & 0 & \sin\omega dt & 0 \\
0 & 0 & 0 & 0 & 1
\end{bmatrix}

.. math::
Q_t & = & \begin{bmatrix}
\frac{dt^3q_x^2}{3} & \frac{dt^2q_x^2}{2} & 0 & 0 & 0 \\
\frac{dt^2q_x^2}{2} & dtq_x^2 & 0 & 0 & 0 \\
0 & 0 & \frac{dt^3q_y^2}{3} & \frac{dt^2q_y^2}{2} & 0 \\
0 & 0 & \frac{dt^2q_y^2}{2} & dtq_y^2 & 0 \\
0 & 0 & 0 & 0 & q_\omega^2
q_x\frac{dt^3}{3} & q_x\frac{dt^2}{2} & 0 & 0 & 0 \\
q_x\frac{dt^2}{2} & q_xdt & 0 & 0 & 0 \\
0 & 0 & q_y\frac{dt^3}{3} & q_y\frac{dt^2}{2} & 0 \\
0 & 0 & q_y\frac{dt^2}{2} & q_ydt & 0 \\
0 & 0 & 0 & 0 & q_\omega dt
\end{bmatrix}
"""
linear_noise_coeffs: np.ndarray = Property(
Expand Down Expand Up @@ -131,7 +131,7 @@ def covar(self, time_interval, **kwargs):

Q = np.array([[dt**3 / 3., dt**2 / 2.],
[dt**2 / 2., dt]])
C = block_diag(Q*q_x**2, Q*q_y**2, q**2)
C = block_diag(Q*q_x, Q*q_y, dt*q)

return CovarianceMatrix(C)

Expand Down
2 changes: 1 addition & 1 deletion stonesoup/models/transition/tests/conftest.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -37,7 +37,7 @@ def covar(linear_noise_coeffs, turn_noise_coeff, time_interval):

Q = np.array([[dt**3 / 3., dt**2 / 2.],
[dt**2 / 2., dt]])
C = block_diag(Q*q_x**2, Q*q_y**2, q**2/dt)
C = block_diag(Q*q_x, Q*q_y, q*dt)

return C

Expand Down
24 changes: 12 additions & 12 deletions stonesoup/updater/tests/test_iterated.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -79,18 +79,18 @@ def test_diekf():
# Check state vector is correct
assert np.allclose(
updated_state.state_vector,
StateVector([[1.810], [1.203], [0.605], [0.901], [0.]]),
StateVector([[1.812], [1.211], [0.603], [0.897], [0.]]),
atol=1e-3)

# Check covariance matrix is correct
assert np.allclose(
updated_state.covar,
CovarianceMatrix(
[[0.666, 0.167, 0.011, 0.002, 0.],
[0.167, 0.427, 0.002, -0.007, -0.008],
[0.011, 0.002, 1.604, 0.401, 0.],
[0.002, -0.007, 0.401, 0.486, 0.008],
[0., -0.008, 0., 0.008, 0.009]]),
[[0.669, 0.174, 0.012, 0.003, 0.],
[0.174, 0.467, 0.003, -0.008, -0.009],
[0.012, 0.003, 1.615, 0.420, 0.],
[0.003, -0.008, 0.420, 0.531, 0.009],
[0., -0.009, 0., 0.009, 0.044]]),
atol=1.e-3)

prediction = sub_predictor.predict(updated_state, time3)
Expand All @@ -102,14 +102,14 @@ def test_diekf():

assert np.allclose(
updated_state.state_vector,
StateVector([[2.555], [1.010], [1.226], [0.820], [0.002]]),
StateVector([[2.550], [0.999], [1.215], [0.811], [0.005]]),
atol=1e-3)
assert np.allclose(
updated_state.covar,
CovarianceMatrix(
[[5.904e-01, 2.501e-01, 2.800e-02, 3.878e-04, -5.127e-03],
[2.501e-01, 2.984e-01, -4.381e-03, -2.161e-02, -1.362e-02],
[2.800e-02, -4.381e-03, 2.121e+00, 6.620e-01, 9.775e-03],
[3.878e-04, -2.161e-02, 6.620e-01, 4.395e-01, 1.740e-02],
[-5.127e-03, -1.362e-02, 9.775e-03, 1.740e-02, 1.107e-02]]),
[[0.603, 0.275, 0.027, -0.003, -0.010],
[0.275, 0.370, -0.013, -0.043, -0.037],
[0.027, -0.013, 2.182, 0.730, 0.022],
[-0.003, -0.043, 0.730, 0.548, 0.049],
[-0.010, -0.037, 0.022, 0.049, 0.078]]),
atol=1e-3)