Kalman filtering : theory and practice using MATLAB
Author(s)
Bibliographic Information
Kalman filtering : theory and practice using MATLAB
Wiley, c2001
2nd ed
- : cloth
Available at 24 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
"A Wiley-Interscience publication"
"The first edition of this book was published by Prentice-Hall in 1993."--Pref
Includes bibliographical references (p. 381-393) and index
Description and Table of Contents
Description
"...an authentic magnum opus worth much more than its weight in gold!" IEEE Transactions on Automatic Control, from a review of the First Edition "The best book I've seen on the subject of Kalman filtering ...Reading other books on Kalman filters and not this one could make you a very dangerous Kalman filter engineer." Amazon.com, from a review of the First Edition In this practical introduction to Kalman filtering theory and applications, 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 provide many illustrative examples drawn from an array of application areas including GPS-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, including techniques for: Representing the problem in a mathematical model Analyzing estimator performance as a function of model parameters Implementing the mechanization equations in numerically stable algorithms Assessing computational requirements Testing the validity of results Monitoring filter performance in operation As the best way to understand and master a technology is to observe it in action, Kalman Filtering: Theory and Practice Using MATLAB(r), Second Edition includes companion software in MATLAB(r), providing users with an opportunity to experience first hand the filter's workings and its limitations. 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, power systems, and biomedical instrumentation.
Table of Contents
Preface. Acknowledgments. General Information. Linear Dynamic Systems. Random Processes and Stochastic Systems. Linear Optimal Filters and Predictors. Nonlinear Applications. Implementation Methods. Practical Considerations. Appendix A: MATLAB Software. Appendix B: A Matrix Refresher. References. Index.
by "Nielsen BookData"