Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises and Solutions / Edition 3

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Overview

In this updated edition the main thrust is on applied Kalman filtering. Chapters 1-3 provide a minimal background in random process theory and the response of linear systems to random inputs. The following chapter is devoted to Wiener filtering and the remainder of the text deals with various facets of Kalman filtering with emphasis on applications. Starred problems at the end of each chapter are computer exercises. The authors believe that programming the equations and analyzing the results of specific examples is the best way to obtain the insight that is essential in engineering work.
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Product Details

  • ISBN-13: 9780471128397
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 11/28/1996
  • Edition description: REV
  • Edition number: 3
  • Pages: 496
  • Product dimensions: 7.00 (w) x 10.00 (h) x 1.00 (d)

Table of Contents

Probability and Random Variables: A Review.

Mathematical Description of Random Signals.

Response of Linear Systems to Random Inputs.

Wiener Filtering.

The Discrete Kalman Filter, State-Space Modeling, and Simulation.

Prediction, Applications, and More Basics on Discrete Kalman Filtering.

The Continuous Kalman Filter.

Smoothing.

Linearization and Additional Intermediate-Level Topics on Applied Kalman Filtering.

More on Modeling: Integration of Noninertial Measurements Into INS.

The Global Positioning System: A Case Study.

Appendices.

Index.

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