It would be nice to have a version of the UKF that can handle dynamics on the form $f(x, u, w, p, t)$ where both $w$ and uncertainty in $p$ are treated by creating sigmapoints for $[x, w, p]$ instead of just adding $R_1$ after the propagation of sigmapoints based on $x$ only.
This would allow modeling non-additive noise as well as uncertain parameters. It's unclear if using this to model uncertain parameters would offer any improvement over adding the uncertain parameter as a state to be estimated, but it would be useful for the non-additive noise.
It would be nice to have a version of the UKF that can handle dynamics on the form $f(x, u, w, p, t)$ where both $w$ and uncertainty in $p$ are treated by creating sigmapoints for $[x, w, p]$ instead of just adding $R_1$ after the propagation of sigmapoints based on $x$ only.
This would allow modeling non-additive noise as well as uncertain parameters. It's unclear if using this to model uncertain parameters would offer any improvement over adding the uncertain parameter as a state to be estimated, but it would be useful for the non-additive noise.