This is one of the best engineering textbooks I have read, period. Although the subject matter is not for the faint-hearted, the authors' attention to pedagogical details shine throughout (repetition is the key to learning). The Kalman filter is introduced naturally as a consequence of a general framework for obtaining the best linear estimator of a random variable given others (earlier observations), and the geometric intuition is stressed repeatedly.
No important issue is omitted, including a very complete treatment of numerical issues and fast algorithms. My only gripe is with the assumption that all model parameters are KNOWN; in other words, the important aspect system identification… Read more