Kalman Filtering: Theory And Practice Using Matlab [with Cdrom]

"An authentic magnum opus worth much more than its weight in gold!"
--IEEE Transactions on Automatic Control

The proven textbook on Kalman filtering--now fully updated, revised, and expanded

This book successfully provides readers with a solid introduction to the theoretical and practical aspects of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common problems, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples drawn from an array of application areas including GNSS-aided INS, the modeling of gyros and accelerometers, inertial navigation, and freeway traffic control. In addition, they share many hard-won lessons about, and original methods for, designing, implementing, validating, and improving Kalman filters.

This Third Edition has been updated with the latest developments in the implementation and application of Kalman filtering, including adaptations for nonlinear filtering, more robust smoothing methods, and developing applications in navigation. All software is provided in MATLAB, giving readers the opportunity to discover how the Kalman filter works in action and to consider the practical arithmetic needed to preserve the accuracy of results.

This updated and revised edition of Grewal and Andrews's classic guide is an indispensable working resource for engineers and computer scientists involved in the design of aerospace and aeronautical systems, global positioning and radar tracking systems, navigation, power systems, and biomedical instrumentation.

Kalman Filtering: Theory and Practice Using MATLAB, Third Edition serves as an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.

This is the Third Edition of a successful textbook and professional reference on Kalman filtering theory and applications. Organized for use at the senior undergraduate level and as a first-year, graduate-level course, this book includes real-world problems in practice as illustrative examples and also covers the more practical aspects of implementation. This updated edition includes a number of new problems and chapters.