9781563474552-1563474557-Fundamentals of Kalman Filtering: A Practical Approach (Progress in Astronautics & Aeronautics)

Fundamentals of Kalman Filtering: A Practical Approach (Progress in Astronautics & Aeronautics)

ISBN-13: 9781563474552
ISBN-10: 1563474557
Author: Paul Zarchan, Howard Musoff
Publication date: 2001
Publisher: Amer Inst of Aeronautics &
Format: Hardcover 664 pages
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Book details

ISBN-13: 9781563474552
ISBN-10: 1563474557
Author: Paul Zarchan, Howard Musoff
Publication date: 2001
Publisher: Amer Inst of Aeronautics &
Format: Hardcover 664 pages

Summary

Fundamentals of Kalman Filtering: A Practical Approach (Progress in Astronautics & Aeronautics) (ISBN-13: 9781563474552 and ISBN-10: 1563474557), written by authors Paul Zarchan, Howard Musoff, was published by Amer Inst of Aeronautics & in 2001. With an overall rating of 3.7 stars, it's a notable title among other Internet, Groupware, & Telecommunications (Networking & Cloud Computing, Aerospace, Engineering, Telecommunications & Sensors, Aeronautics & Astronautics, Astronomy & Space Science, Mathematics) books. You can easily purchase or rent Fundamentals of Kalman Filtering: A Practical Approach (Progress in Astronautics & Aeronautics) (Hardcover) from BooksRun, along with many other new and used Internet, Groupware, & Telecommunications books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.32.

Description

This text is a practical guide to building Kalman filters and shows how the filtering equations can be applied to real-life problems. Numerous examples are presented in detail showing the many ways in which Kalman filters can be designed. Computer code written in FORTRAN, MATLAB®, and True BASIC accompanies all of the examples so that the interested reader can verify concepts and explore issues beyond the scope of the text.

Sometimes mistakes are introduced intentionally to the initial filter designs in order to show the reader what happens when the filter is not working properly. The text spends a great deal of time setting up a problem before the Kalman filter is actually formulated in order to give the reader an intuitive feel for the problem being addressed. Real problems are seldom presented in the form of differential equations and they usually don’t have unique solutions. Therefore, the authors illustrate several different filtering approaches for tackling a problem. Readers will gain experience in software and performance tradeoffs for determining the best filtering approach for the application at hand.

MATLAB is a registered trademark of The MathWorks, Inc.

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