Advanced Kalman Filtering, Least-Squares and Modeling: A Practical Handbook

Bruce P. Gibbs

ISBN 10: 0470529709 / ISBN 13: 9780470529706

Published by John Wiley & Sons Inc, 2011

About this Item

This book is intended primarily as a handbook for engineers who must design practical systems. Its primary goal is to discuss model development in sufficient detail so that the reader may design an estimator that meets all application requirements and is robust to modeling assumptions. Num Pages: 632 pages, Illustrations. BIC Classification: TJFM. Category: (P) Professional & Vocational. Dimension: 258 x 182 x 39. Weight in Grams: 1378. . 2011. 1st Edition. Hardcover. . . . .

Seller Inventory # V9780470529706

Bibliographic Details

• Title: Advanced Kalman Filtering, Least-Squares and Modeling: A Practical Handbook
• Publisher: John Wiley & Sons Inc
• Publication Date: 2011
• Language: English
• ISBN 10: 0470529709
• ISBN 13: 9780470529706
• Binding: Hardcover
• Edition: 1st Edition
• Condition: New

About this title

Synopsis

This book provides a complete explanation of estimation theory and application, modeling approaches, and model evaluation. Each topic starts with a clear explanation of the theory (often including historical context), followed by application issues that should be considered in the design. Different implementations designed to address specific problems are presented, and numerous examples of varying complexity are used to demonstrate the concepts.

This book is intended primarily as a handbook for engineers who must design practical systems.  Its primary goal is to explain all important aspects of Kalman filtering and least-squares theory and application.  Discussion of estimator design and model development is emphasized so that the reader may develop an estimator that meets all application requirements and is robust to modeling assumptions.  Since it is sometimes difficult to a priori determine the best model structure, use of exploratory data analysis to define model structure is discussed.  Methods for deciding on the "best" model are also presented.

A second goal is to present little known extensions of least squares estimation or Kalman filtering that provide guidance on model structure and parameters, or make the estimator more robust to changes in real-world behavior.

A third goal is discussion of implementation issues that make the estimator more accurate or efficient, or that make it flexible so that model alternatives can be easily compared.

The fourth goal is to provide the designer/analyst with guidance in evaluating estimator performance and in determining/correcting problems.

The final goal is to provide a subroutine library that simplifies implementation, and flexible general purpose high-level drivers that allow both easy analysis of alternative models and access to extensions of the basic filtering.

About the Author

BRUCE P. GIBBS has forty-one years of experience applying estimation and control theory to applications for NASA, the Department of Defense, the Department of Energy, the National Science Foundation, and private industry. He is currently a consulting scientist at Carr Astronautics, where he designs image navigation software for the GOES-R geosynchronous weather satellite. Gibbs previously developed similar systems for the GOES-NOP weather satellites and GPS.