[Bayes++] Bayes++ w/EKF and a non-linear equation: How to model?

[Michael S. <ms...@21...>]

Hello, everyone.

I am attempting to use the Covariance_filter as an EKF for a non-linear
model. However, I do not understand which type of model class to use,
and how to specify the data for the models, even after looking at the
Bayesian Filtering overview. I'm pretty sure I need to use a
linrz_predict_model (or something like that) but beyond that...

The main problem is that the elements of the f function I want to use
for the model are exponential. It's non-linear, with noise, but no
control (it's essentially 'the object I'm trying to predict is walking
around randomly, but within the laws of physics') How do you specify
that? I've been looking at the Welch and Bishop introduction and trying
to compare back to Bayes++, but with no avail. I'm fairly sure I could
use the libraries if my model was linear, but I don't quite see how to
put the non-linearity in there. The documentation doesn't make it
completely clear what all the pieces that I'm specifying are. Is there
any help anyone could offer?

Thanks,
Mike Simon