Kalman Filtering

with Real-Time Applications

  • Charles K. Chui
  • Guanrong Chen

Part of the Springer Series in Information Sciences book series (SSINF, volume 17)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Charles K. Chui, Guanrong Chen
    Pages 1-19
  3. Charles K. Chui, Guanrong Chen
    Pages 20-32
  4. Charles K. Chui, Guanrong Chen
    Pages 33-48
  5. Charles K. Chui, Guanrong Chen
    Pages 49-66
  6. Charles K. Chui, Guanrong Chen
    Pages 67-76
  7. Charles K. Chui, Guanrong Chen
    Pages 77-96
  8. Charles K. Chui, Guanrong Chen
    Pages 97-107
  9. Charles K. Chui, Guanrong Chen
    Pages 108-130
  10. Charles K. Chui, Guanrong Chen
    Pages 131-142
  11. Charles K. Chui, Guanrong Chen
    Pages 143-157
  12. Back Matter
    Pages 158-195

About this book

Introduction

In addition to making a number of minor corrections and updat­ ing the references, we have expanded the section on "real-time system identification" in Chapter 10 of the first edition into two sections and combined it with Chapter 8. In its place, a very brief introduction to wavelet analysis is included in Chapter 10. Although the pyramid algorithms for wavelet decompositions and reconstructions are quite different from the Kalman filtering al­ gorithms, they can also be applied to time-domain filtering, and it is hoped that splines and wavelets can be incorporated with Kalman filtering in the near future. College Station and Houston Charles K. Chui September 1990 Guanrong Chen Preface to the First Edition Kalman filtering is an optimal state estimation process applied to a dynamic system that involves random perturbations. More precisely, the Kalman filter gives a linear, unbiased, and min­ imum error variance recursive algorithm to optimally estimate the unknown state of a dynamic system from noisy data taken at discrete real-time. It has been widely used in many areas of industrial and government applications such as video and laser tracking systems, satellite navigation, ballistic missile trajectory estimation, radar, and fire control. With the recent development of high-speed computers, the Kalman filter has become more use­ ful even for very complicated real-time applications.

Keywords

Algebra Kalman filtering Kalman-Filter Nonlinear systems System identification Wavelet algorithm algorithms filters linear algebra systems theory

Authors and affiliations

  • Charles K. Chui
    • 1
  • Guanrong Chen
    • 2
  1. 1.Department of Mathematics and Department of Electrical EngineeringTexas A&M UniversityCollege StationUSA
  2. 2.Department of Electrical EngineeringUniversity of HoustonHoustonUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-02666-3
  • Copyright Information Springer-Verlag Berlin Heidelberg 1991
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-54013-7
  • Online ISBN 978-3-662-02666-3
  • Series Print ISSN 0720-678X
  • About this book