Kalman Filtering

1. Front Matter

   Pages I-XIV

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2. Preliminaries

   • Charles K. Chui, Guanrong Chen

   Pages 1-19

3. Kalman Filter: An Elementary Approach

   • Charles K. Chui, Guanrong Chen

   Pages 20-32

4. Orthogonal Projection and Kalman Filter

   • Charles K. Chui, Guanrong Chen

   Pages 33-48

5. Correlated System and Measurement Noise Processes

   • Charles K. Chui, Guanrong Chen

   Pages 49-66

6. Colored Noise

   • Charles K. Chui, Guanrong Chen

   Pages 67-76

7. Limiting Kalman Filter

   • Charles K. Chui, Guanrong Chen

   Pages 77-96

8. Sequential and Square-Root Algorithms

   • Charles K. Chui, Guanrong Chen

   Pages 97-107

9. Extended Kalman Filter and System Identification

   • Charles K. Chui, Guanrong Chen

   Pages 108-130

10. Decoupling of Filtering Equations

    • Charles K. Chui, Guanrong Chen

    Pages 131-142

11. Kalman Filtering for Interval Systems

    • Charles K. Chui, Guanrong Chen

    Pages 143-163

12. Wavelet Kalman Filtering

    • Charles K. Chui, Guanrong Chen

    Pages 164-177

13. Notes

    • Charles K. Chui, Guanrong Chen

    Pages 178-190

14. Back Matter

    Pages 191-230

    PDF

Kalman Filtering with Real-Time Applications 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. The last two topics are new additions to this third edition. 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 knowled

• Filtering
• Interval Sytem
• Mathematica
• Optical Estimation
• Signal
• Wavelet
• algorithm
• algorithms
• filters

To summarize, the authors have succeeded in bringing together the mathematical theory and the needs of practitioners. The newly added chapters, in particular the one on wavelets, give the book a proper finish. For a book of this size, it leaves little to be desired. It presetns a wealth of details while at the same time avoiding unnecessary abstraction. Andreas Ruppin, Berlin, Germany (SSN Stat. Software News, 2000, 34,3-4

• Department of Mathematics, and Department of Electrical Engineering, Texas A&M University, College Station, USA

  Charles K. Chui

• Department of Electrical and Computer Engineering, University of Houston, Houston, USA

  Guanrong Chen

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