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Kalman filtering : theory and practice using MATLAB / Mohinder S. Grewal and Angus P. Andrews.

By: Contributor(s): Material type: TextTextPublication details: New Jersey : John Wiley, ©2015.Edition: 4th edDescription: xvii, 617 p. : illustrations ; 24 cmISBN:
  • 9781118851210
Subject(s): DDC classification:
  • 629.8312 23 G841
Contents:
1. Introduction -- 2. Linear dynamic systems -- 3. Probability and expectancy -- 4. Random processes -- 5. Linear optimal filters and predictors -- 6. Optimal smoothers -- 7. Implementation methods -- 8. Nonlinear approximations -- 9. Practical considerations -- 10. Applications to navigation -- Appendix A: software -- Index.
Summary: This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitation of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, fourth edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this topic.
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Includes bibliographical references and index.

1. Introduction --
2. Linear dynamic systems --
3. Probability and expectancy --
4. Random processes --
5. Linear optimal filters and predictors --
6. Optimal smoothers --
7. Implementation methods --
8. Nonlinear approximations --
9. Practical considerations --
10. Applications to navigation --
Appendix A: software --
Index.

This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitation of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, fourth edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this topic.

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