- Hardcover: 416 pages
- Publisher: Wiley-Interscience; 2 edition (Jan 2 2001)
- Language: English
- ISBN-10: 0471392545
- ISBN-13: 978-0471392545
- Product Dimensions: 23.8 x 15.8 x 2.8 cm
- Shipping Weight: 762 g
- Average Customer Review: 2.5 out of 5 stars See all reviews (4 customer reviews)
- Amazon Bestsellers Rank: #1,571,058 in Books (See Top 100 in Books)
- See Complete Table of Contents
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Product Details |
Product Description
Review
"This book could serve as an introduction to stochastic/random processes...practicing engineers with enough mathematical background would appreciate this book...academicians and scientists would also find this book very useful." (IEEE Circuits & Devices Magazine, July 2003)
"Provides readers with a working familiarity with both the theoretical and practical aspects of Kalman filtering." (SciTech Book News, Vol. 25, No. 3, September 2001)
Product Description
". . . 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(r), Second Edition includes companion software in MATLAB(r), 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.
"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(r), Second Edition includes companion software in MATLAB(r), 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.
An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Inside This Book
(Learn More)
First Sentence
Theoretically the Kalman Filter is an estimator for what is called the linear-quadratic problem, which is the problem of estimating the instantaneous "state" (a concept that will be made more precise in the next chapter) of a linear dynamic system perturbed by white noise-by using measurements linearly related to the state but corrupted by white noise. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
Theoretically the Kalman Filter is an estimator for what is called the linear-quadratic problem, which is the problem of estimating the instantaneous "state" (a concept that will be made more precise in the next chapter) of a linear dynamic system perturbed by white noise-by using measurements linearly related to the state but corrupted by white noise. Read the first page
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Browse Sample PagesConcordance
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Customer Reviews
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Most helpful customer reviews
2 of 2 people found the following review helpful
2.0 out of 5 stars
Insufficient,
This review is from: Kalman Filtering: Theory and Practice Using MATLAB (Hardcover)
While the book does cover material from a wide variety of sub-topics related to Kalman filtering, much of this is presented in a disjointed and ill-explained manner.Regarding some important topics such as state augmentation and parameter estimation, the book is utterly deficient in conveying useful information to the reader: In both of these cases, the book presents only a single example of each, and neither of these are followed to completion. In both cases the author simply refers to code on the CD which has an implementation of the problem at hand - a practice which I find unacceptable given the difficulty of pulling a formula, and general best practice advice out of code. Additionally, concerning linearization for extended or linearized kalman filters the book also only has one example, and this is a trivial exercise as the problem is 1-dimensional. In the back of the edition I have there are over Two hundred and thirty references to secondary sources, which helps explain why the first three chapters are so very reminiscient of Gelb, and why problem 5.9 appears to be verbatim from Brown and Hwang (who themselves have taken it from Sorensen). A final frustration is the chapter problems are presented without solutions, so unless you are a professor or a practicing engineer the book will only serve to undermine your confidence as it will provide zero feedback on your execution of the task at hand.
2.0 out of 5 stars
Not enough examples...,
By A Customer
This review is from: Kalman Filtering: Theory and Practice Using MATLAB (Hardcover)
This book is difficult to understand due to the lack of simple examples to illustrate keep points as they are introduced.There are a few examples in each chapter, however the authors skip too many steps and make you constantly flip around in the book to review previous examples upon which he bases the new examples. The end result is just wasteful trashing by the student. This is a good book, but it does't have enough textbook examples to be used for an intro class in Kalam filtering. Maybe this book would be useful as a secondary reference for a person that already knows Kalman filtering.
5.0 out of 5 stars
Most useful text on the subject,
By A Customer
This review is from: Kalman Filtering: Theory and Practice Using MATLAB (Hardcover)
I have been working with "Kalman Fitering, ... Using Matlab",2nd Edition, for several weeks, and I must tell you it is by far the most useful text on the subject.
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