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New example that shows linearised ODE as transition model #1009
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Codecov ReportAll modified and coverable lines are covered by tests ✅
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## main #1009 +/- ##
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+ Coverage 93.72% 93.74% +0.02%
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Lines 14004 14004
Branches 1925 1925
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+ Partials 252 251 -1
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# %% | ||
# 2. Create the linearised function; | ||
# ---------------------------------- | ||
# We have create a series of detections from a target moving with peculiar dynamics as can be seen |
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# We have create a series of detections from a target moving with peculiar dynamics as can be seen | |
# We have created a series of detections from a target moving with peculiar dynamics as can be seen |
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Just a small grammatical change.
# nearly constant heading transition model [2]_. | ||
# | ||
# We can use Stone Soup components to create a linearised model and use standard components to | ||
# perform the tracking. This method can be used in other context such as space domain (i.e., |
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# perform the tracking. This method can be used in other context such as space domain (i.e., | |
# perform the tracking. This method can be used in other contexts such as the space domain (i.e., |
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Added the comments @csherman-dstl made, rebased the branch and fixed the conflict with the new 1.5 stone soup version |
(x, vx, s, vy, theta) = state | ||
# generate the s component | ||
s = torch.sqrt(vx*vx + vy*vy) | ||
return s * torch.cos(theta), 0 * s, s * torch.sin(theta), 0. * s, 0. * theta |
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(x, vx, s, vy, theta) = state | |
# generate the s component | |
s = torch.sqrt(vx*vx + vy*vy) | |
return s * torch.cos(theta), 0 * s, s * torch.sin(theta), 0. * s, 0. * theta | |
(x, vx, y, vy, theta) = state | |
# generate the s component | |
s = torch.sqrt(vx*vx + vy*vy) | |
return s * torch.cos(theta), 0. * s, s * torch.sin(theta), 0. * s, 0. * theta |
Just a small last thing that I noticed. Is the s
taken from the state supposed to be a y
. (the variable isn't used so it doesn't change anything)
This PR follows the (now closed #952) where I changed the example from a space domain case to a navigation like transition model (constant heading).
The example provides a snapshot on how to linearise a non-linear time variant transition model using the Van Loan method.
Some feedback on the document provided in the previous PR are incomporated already.
The example considered mimics the one presented in the following paper:
[1] Kountouriotis, Panagiotis-Aristidis, and Simon Maskell. "Maneuvering target tracking using an unbiased nearly constant heading model." 2012 15th International Conference on Information Fusion. IEEE, 2012.
(https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6290578.)