Preliminaries --; Kalman Filter: An Elementary Approach --; Orthogonal Projection and Kalman Filter --; Correlated System and Measurement Noise Processes --; Colored Noise --; Limiting Kalman Filter --; Sequential and Square-Root Algorithms --; Extended Kalman Filter and System Identification --; Decoupling of Filtering Equations --; Notes --; References --; Answers and Hints to Exercises --; Subject Index.
SUMMARY OR ABSTRACT
Text of Note
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, system 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.