Kalman Filtering: Theory and Practice Using Matlab

Grewal (California State U. at Fullerton) and Andrews, retired from the Rockwell Science Center, explain the theoretical and practical aspects of Kalman filtering through practice and real world examples, and in this edition include important developments in applications of filtering over the past several years, including adaptations for nonlinear filtering, more robust methods of assessment, and new applications in navigation. They cover linear dynamics systems, random processes and stochastic systems, linear filters and predictors, optimal smoothers, implementation methods, nonlinear filtering, practical considerations, and applications, and include an appendix on matrices. The authors provide all necessary software, making this a text suitable for first year graduate courses on common filtering theory and application, or in a basic course in digital estimation theory and application. This is so well-written it can be used as a self-study guide. Annotation c2008 Book News, Inc., Portland, OR (booknews.com)

Mohinder S. Grewal, PhD, PE, is Professor of Electrical Engineering in the College of Engineering and Computer Science at California State University, Fullerton. He has more than thirty-five years of experience in inertial navigation and control, and his mechanizations are currently used in commercial and military aircraft, surveillance satellites, missile and radar systems, freeway traffic control, and the Global Navigation Satellite System.

Angus P. Andrews, PhD, is a retired senior scientist from the Rockwell Science Center. His experience with aerospace systems analysis and design using Kalman filters began with his involvement in the Apollo moon project, and he is credited with the discovery of unknown landmark tracking as an orbital navigation method.