Kalman Filtering: With Real-Time Applications (Springer Series in Information Sciences)

This book presents a thorough discussion of the mathematical theory of Kalman filtering. The filtering equations are derived in a series of elementary steps enabling the optimality of the process to be understood. It provides a comprehensive treatment of various major topics in Kalman-filtering theory, including uncorrelated and correlated noise, colored noise, steady-state theory, nonlinear systems, systems identification, numerical algorithms, and real-time applications. A series of problems for the student, together with a complete set of solutions, are also included. The style of the book is informal, and the mathematics elementary but rigorous, making it accessible to all those with a minimal knowledge of linear algebra and systems theory. In this second edition, in addition to some minor corrections and up-dating, the section on real-time system identification has been expanded and a brief introduction to wavelet analysis included.