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

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Overview

The Fourth Edition to the Introduction of Random Signals and Applied Kalman Filtering is updated to cover innovations in the Kalman filter algorithm and the proliferation of Kalman filtering applications from the past decade. The text updates both the research advances in variations on the Kalman filter algorithm and adds a wide range of new application examples. Several chapters include a significant amount of new material on applications such as simultaneous localization and mapping for autonomous vehicles, inertial navigation systems and global satellite navigation systems.

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Editorial Reviews

Booknews
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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Product Details

  • ISBN-13: 9780470609699
  • Publisher: Wiley
  • Publication date: 2/7/2012
  • Series: CourseSmart Series
  • Edition description: New Edition
  • Edition number: 4
  • Pages: 400
  • Product dimensions: 7.20 (w) x 10.10 (h) x 0.80 (d)

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

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