There is also a class at Stanford that builds up all the theory of the Kalman filter, starting with elementary probability [1]. The slides are all posted, and while they wouldn&#x27;t be great to learn the material from, they&#x27;re an excellent reference (and go into more depth on multivariate Gaussians and estimation theory than Probabilistic Robotics).<p>1. <a href="http:&#x2F;&#x2F;engr207b.stanford.edu&#x2F;" rel="nofollow">http:&#x2F;&#x2F;engr207b.stanford.edu&#x2F;</a>