Kalman filtering is a 50 year old technique to obtain the "optimal" state estimate of a system that may change with time. It does this by using a two-step recursion: a prediction phase and a measurement phase. There are are several well written resources to understand Kalman Filtering such as this and this . It would be silly and unnecessary for me to try and explain that same standard material here. However, I recently developed a slightly different intuition to understand the principles behind Kalman filtering. I am fairly certain that I am extremely unlikely to be the only one with this explanation. However, since I could not find similar material on the internet while searching for Kalman filters, it should be of some use to those who land on this page. In the physical world, every observation/prediction is error-prone. My old professor, Dr. P. Subbanna Bhat liked to say that "God and noise are omnipotent". I don't know about God, but noise definit...