[havercosine]

This is a great post. Another aha! moment I had in understanding Kalman Filter came from a short note by John D. Cook (link: https://www.johndcook.com/blog/applied-kalman-filtering/) . A traditional calculus/differential equations based modelling of systems takes a view that there is no uncertainty in the data and everything is captured by system model. OTOH, data driven estimator will say that "it is all in the data", completely ignoring the model of the physical process that is generating the data. Beauty of Kalman filters is that it combines these two approaches.