Kalman Filtering: Theory and Practice Using MATLAB

[NAUTILUS87]

Kalman Filtering: Theory and Practice Using MATLAB

Kalman Filtering: Theory and Practice Using MATLAB By Mohinder S. Grewal, Angus P. Andrews
Publisher: Wiley-Interscience 2001 | 416 Pages | ISBN: 0471392545 | PDF | 3 MB

". . . an authentic magnum opus worth much more than its weight in gold!"-IEEE Transactions on Automatic Control, from a review of the First Edition
"The best book I've seen on the subject of Kalman filtering . . . Reading other books on Kalman filters and not this one could make you a very dangerous Kalman filter engineer."-Amazon.com, from a review of the First Edition
In this practical introduction to Kalman filtering theory and applications, authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common problems, and limitations of estimation theory as it applies to real-world situations. They provide many illustrative examples drawn from an array of application areas including GPS-aided INS, the modeling of gyros and accelerometers, inertial navigation, and freeway traffic control. In addition, they share many hard-won lessons about, and original methods for, designing, implementing, validating, and improving Kalman filters, including techniques for:
* Representing the problem in a mathematical model
* Analyzing estimator performance as a function of model parameters
* Implementing the mechanization equations in numerically stable algorithms
* Assessing computational requirements
* Testing the validity of results
* Monitoring filter performance in operation
As the best way to understand and master a technology is to observe it in action, Kalman Filtering: Theory and Practice Using MATLAB®, Second Edition includes companion software in MATLAB®, providing users with an opportunity to experience first hand the filter's workings and its limitations.
This updated and revised edition of Grewal and Andrews's classic guide is an indispensable working resource for engineers and computer scientists involved in the design of aerospace and aeronautical systems, global positioning and radar tracking systems, power systems, and biomedical instrumentation.

Note from Nautilus87 : This book is used for Structural Health Monitoring

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[andersen3]

Kalman Filtering: Theory and Practice Using MATLAB ed3

Author: MOHINDER S. GREWAL; ANGUS P. ANDREWS | Size: 5.05 MB | Format: PDF | Quality: Original preprint | Publisher: John Wiley & Sons | Year: 2008 | pages: 581 | ISBN: 9780470173664

This book is designed to provide familiarity with both thetheoretical andpractical aspects of Kalman filtering by including real-world problems in practice as illustrative examples. The material includes the essential technical background for Kalman filter-ing and the more practical aspects of implementation: how to represent the problem in a mathematical model, analyze the performance of the estimator as a function of system design parameters, implement the mechanization equations in numerically stable algorithms, assess its computational requirements, test the validity of results, and monitor the filter performance in operation. These are important attributes of the subject that are often overlooked in theoretical treatments but are necessary for application of the theory to real-world problems.
In this third edition, we have included important developments in the implemen-tation and application of Kalman filtering over the past several years, including adap-tations for nonlinear filtering, more robust smoothing methods, and developing applications in navigation.
We have also incorporated many helpful corrections and suggestions from our readers, reviewers, colleagues, and students over the past several years for the overall improvement of the textbook.
All software has been provided in MATLAB so that users can take advantage of its excellent graphing capabilities and a programming interface that is very close to the mathematical equations used for defining Kalman filtering and its applications.

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link dead for ed1; another link here for ed1:

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