The definitive textbook and professional reference on Kalman Filtering – fully updated, revised, and expanded
This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control.
Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is 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.
Keywords: Kalman filter; linear dynamic systems; matrix; random processes; probability distribution; linear optimal filters; predictors; optimal smoothers; nonlinear extensions; navigation; inertial navigation systems; Global Navigation Satellite Systems, Signal Processing, Remote Sensing, Signal Processing, Remote Sensing