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Kalman Filtering

with Real-Time Applications

Authors: Chui, Charles K., Chen, Guanrong

  • Provides a rigorous and concise introduction to Kalman filtering, now expanded and fully updated in its 5th edition
  • Includes many end-of-chapters exercises, as well as a section at the end of the book with solutions and hints
  • Also of interest to practitioners with a strong mathematical background who will be building Kalman filters and smoothers
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Buy this book

eBook $54.99
price for USA (gross)
  • ISBN 978-3-319-47612-4
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $69.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: June 8, 2017
  • ISBN 978-3-319-47610-0
  • Free shipping for individuals worldwide
About this Textbook

This new edition presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering. Over 100 exercises and problems with solutions help deepen the knowledge. This new edition has a new chapter on filtering communication networks and data processing, together with new exercises and new real-time applications.

About the authors

Prof. Dr. Charles K. Chui, Stanford University, Stanford, CA, USA

Prof. Dr. Guanrong Chen, City Univesity Hong Kong, Kowloon, Hong Kong, PR China

Reviews

“Kalman filtering (KF) is a wide class of algorithms designed, in words selected from this outstanding book, ‘to obtain an optimal estimate’ of the state of a system from information in the presence of noise. … It is also written to serve as a reference for engineers … . The book has my highest recommendation, and it will reward readers for careful and iterative study of its text and well-designed exercises.” (Computing Reviews, October, 2017)


Table of contents (13 chapters)

  • Preliminaries

    Chui, Charles K. (et al.)

    Pages 1-18

  • Kalman Filter: An Elementary Approach

    Chui, Charles K. (et al.)

    Pages 19-31

  • Orthogonal Projection and Kalman Filter

    Chui, Charles K. (et al.)

    Pages 33-49

  • Correlated System and Measurement Noise Processes

    Chui, Charles K. (et al.)

    Pages 51-68

  • Colored Noise Setting

    Chui, Charles K. (et al.)

    Pages 69-79

Buy this book

eBook $54.99
price for USA (gross)
  • ISBN 978-3-319-47612-4
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $69.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: June 8, 2017
  • ISBN 978-3-319-47610-0
  • Free shipping for individuals worldwide
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Bibliographic Information

Bibliographic Information
Book Title
Kalman Filtering
Book Subtitle
with Real-Time Applications
Authors
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-47612-4
DOI
10.1007/978-3-319-47612-4
Hardcover ISBN
978-3-319-47610-0
Edition Number
5
Number of Pages
XVIII, 247
Number of Illustrations and Tables
34 b/w illustrations
Additional Information
Originally published as volume 17 in the series: Springer Series in Information Sciences
Topics