Kalman Filtering

with Real-Time Applications

Charles K. Chui, Guanrong Chen (Autoren)

Buch | Softcover

XVIII, 247 Seiten

2018 | 5. Softcover reprint of the original 5th ed. 2017
Springer International Publishing (Verlag)
978-3-319-83780-2 (ISBN)

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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.

Prof. Dr. Charles K. Chui, Stanford University, Stanford, CA, USA Prof. Dr. Guanrong Chen, City Univesity Hong Kong, Kowloon, Hong Kong, PR China

Preliminaries.- Kalman Filter: An Elementary Approach.- Orthogonal Projection and Kalman Filter.- Correlated System and Measurement Noise Processes.- Colored Noise.- Limiting Kalman Filter.- Sequential and Square-Root Algorithms.- Extended Kalman Filter and System Identification.- Decoupling of Filtering Equations.- Kalman Filtering for Interval Systems.- Wavelet Kalman Filtering.- Distributed Estimation on Sensor Networks.- Notes.- Answers and Hints to Exercises.

"This book is suitable for self-study as well as for use in a one-quarter or one-semester introductory course on Kalman filtering theory for upper-division undergraduate or first-year graduate to applied mathematics or engineering students." (Mikhail P. Moklyachuk, zbMath 1416.93001, 2019)
"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)

Erscheinungsdatum	05.03.2022
Zusatzinfo	XVIII, 247 p. 34 illus.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	4102 g
Themenwelt	Naturwissenschaften ► Physik / Astronomie ► Allgemeines / Lexika
Themenwelt	Naturwissenschaften ► Physik / Astronomie ► Theoretische Physik
Schlagworte	Algorithm Dynamic System • Algorithm Noisy Data • Algorithm Remote Tracking System • Algorithm Satellite Navigation • Control Theory Navigation • Control Theory Positioning • Filtering Communication Networks • Filtering Nonlinear Systems • Textbook Chui • Textbook Kalman Filtering
ISBN-10	3-319-83780-X / 331983780X
ISBN-13	978-3-319-83780-2 / 9783319837802
Zustand	Neuware