Recently we've encountered Kalman filter algorithm for state estimation in a course of Probabilistic Robotics.
After taking several days to try to read Kalman's original paper published in 1960, A New Approach to Linear Filtering and Prediction Problems, it firstly feels a bit difficult to read, and it seems the majority is to show the orthogonal projection is the optimal estimation under certain conditions and solutions to Wiener's problem.
But I did not find the exact algorithm in this original paper as the one in the textbook.
- For example, is there an explanation of "Kalman gain" in this paper ?
- Does Kalman's paper provide a mathematical derivation of Kalman filter algorithm?