[ActorNightly]

When you start dealing with linear systems and disturbances, you end up with basically matrix math and covariance in some form and way.

The thing about Kalman filter is that its a pretty well known and exists in many software packages (just like PID) so its fairly easy to implement. But because noise is often not gaussian, and systems are often not linear, its more of a "works well enough" for most applications.