Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises / Edition 4

by Robert Grover Brown, Patrick Y. C. Hwang

Overview

Advances in computers and personal navigation systems have greatly expanded the applications of Kalman filters. A Kalman filter uses information about noise and system dynamics to reduce uncertainty from noisy measurements. Common applications of Kalman filters include such fast-growing fields as autopilot systems, battery state of charge (SoC) estimation, brain-computer interface, dynamic positioning, inertial guidance systems, radar tracking, and satellite navigation systems.

Brown and Hwang's bestselling textbook introduces the theory and applications of Kalman filters for senior undergraduates and graduate students. This revision updates both the research advances in variations on the Kalman filter algorithm and adds a wide range of new application examples. The book emphasizes the application of computational software tools such as MATLAB. The companion website includes M-files to assist students in applying MATLAB to solving end-of-chapter homework problems.

Product Details

ISBN-13:	9780470609699
Publisher:	Wiley
Publication date:	02/07/2012
Series:	CourseSmart Series
Edition description:	4th ed.
Pages:	400
Product dimensions:	7.20(w) x 10.10(h) x 0.80(d)

About the Author

Robert Grover Brown and Patrick Y. C. Hwang are the authors of Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises, 4th Edition, published by Wiley.

Table of Contents

PART 1: RANDOM SIGNALS BACKGROUND
Chapter 1 Probability and Random Variables: A Review
Chapter 2 Mathematical Description of Random Signals
Chapter 3 Linear Systems Response, State-space Modeling and Monte Carlo Simulation
PART 2: KALMAN FILTERING AND APPLICATIONS
Chapter 4 Discrete Kalman Filter Basics
Chapter 5 Intermediate Topics on Kalman Filtering
Chapter 6 Smoothing and Further Intermediate Topics
Chapter 7 Linearization, Nonlinear Filtering and Sampling Bayesian Filters
Chapter 8 the "Go-Free" Concept, Complementary Filter and Aided Inertial Examples
Chapter 9 Kalman Filter Applications to the GPS and Other Navigation Systems
APPENDIX A. Laplace and Fourier Transforms
APPENDIX B. The Continuous Kalman Filter

Editorial Reviews

A textbook for an introductory course focusing on Kalman filtering. Provides the necessary background in random process theory and the response of linear systems to random inputs; assumes a knowledge of linear systems analysis at the junior or senior level of engineering. The second edition was published sometime before 1992. The 3.5<"> disk for DOS contains software relating to Kalman filtering that is suitable for tutorial but not practical purposes. Annotation c. by Book News, Inc., Portland, Or.

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