| An Introduction to Kalman Filtering with MATLAB Examples Contributor(s): Nowatzki, Narayan (Author), Banavar, Manesh (Author), Spanias, Andreas (Author) |
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ISBN: 1627051392 ISBN-13: 9781627051392 Publisher: Morgan & Claypool OUR PRICE: $38.00 Product Type: Paperback Published: September 2013 * Not available - Not in print at this time * |
| Additional Information |
| BISAC Categories: - Technology & Engineering | Signals & Signal Processing - Technology & Engineering | Robotics - Computers | Programming - Algorithms |
| Dewey: 629.831 |
| Series: Synthesis Lectures on Signal Processing |
| Physical Information: 0.17" H x 7.5" W x 9.25" (0.35 lbs) 81 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications, e.g., target tracking, guidance and navigation, and communications systems. The purpose of this book is to present a brief introduction to Kalman filtering. The theoretical framework of the Kalman filter is first presented, followed by examples showing its use in practical applications. Extensions of the method to nonlinear problems and distributed applications are discussed. A software implementation of the algorithm in the MATLAB programming language is provided, as well as MATLAB code for several example applications discussed in the manuscript. Table of Contents: Acknowledgments / Introduction / The Estimation Problem / The Kalman Filter / Extended and Decentralized Kalman Filtering / Conclusion / Notation / Bibliography / Authors' Biographies |