I am intringued by the use of Kalman Filters in this example. Here the kalman filter is being used to track as well as calibrate using data that comes in sequentially.

I have questions about this paper this time: What is meant by "improve" when the so called isolation enforced by the SCAAT approach improves on situations when individual elements of the constraints are corrupted by indepedent noise over a batch or ensemble estimation scheme? (sec 2.2) I've always learned that the more data points one's got, the better the estimate.

For the 6 states that describes the incremental angle and rate of incremental angle change, we are really looking at the angular velocity of the point and tne angular acceleration. Why do we consider the acceleration for the angles and not the acceleration of the displacements? And this zeroing out the orientaiton elements of the state vector step...what's that for? Shouldn't it's changed be accounted for in the process noise or even the process transition matrix?