Kalman Filtering

with Real-Time Applications
Softcover Nachdruck of the original 5th Auflage 2017
ISBN: 978-3-319-83780-2
Verlag: Springer International Publishing

Buch, Englisch, 247 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 4102 g

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.

Zielgruppe

Graduate

Autoren/Hrsg.

Chen, Guanrong

Chui, Charles K.

Fachgebiete

• Naturwissenschaften Physik Physik Allgemein Theoretische Physik, Mathematische Physik, Computerphysik
• Mathematik | Informatik Mathematik Stochastik Stochastische Prozesse
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung

Inhaltsverzeichnis

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.

Über Autor(innen)

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

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