Optimal Estimation of Dynamic Systems

by John L. Crassidis, John L. Junkins

Overview

An ideal self-study guide for practicing engineers as well as senior undergraduate and beginning graduate students, this book highlights the importance of both physical and numerical modeling in solving dynamics-based estimation problems found in engineering systems, such as spacecraft attitude determination, GPS navigation, orbit determination, and aircraft tracking. With more than 100 pages of new material, this reorganized and expanded edition incorporates new theoretical results, a new chapter on advanced sequential state estimation, and additional examples and exercises. MATLAB codes are available on the book's website.

Product Details

ISBN-13:	9781040059630
Publisher:	CRC Press
Publication date:	10/26/2011
Series:	Advances in Applied Mathematics
Sold by:	Barnes & Noble
Format:	eBook
Pages:	749
File size:	5 MB

About the Author

John L. Crassidis, Ph.D., is a professor of mechanical and aerospace engineering and the associate director of the Center for Multisource Information Fusion at the University at Buffalo, State University of New York. He previously worked at Texas A&M University, the Catholic University of America, and NASA's Goddard Space Flight Center, where he contributed to attitude determination and control schemes for numerous spacecraft missions.

John L. Junkins, Ph.D., is a distinguished professor of aerospace engineering and the founder and director of the Center for Mechanics and Control at Texas A&M University. In addition to his historical contributions in analytical dynamics and spacecraft GNC, Dr. Junkins and his team have designed, developed, and demonstrated several new electro-optical sensing technologies.

Table of Contents

Least Squares Approximation. Probability Concepts in Least Squares. Sequential State Estimation. Advanced Topics in Sequential State Estimation. Batch State Estimation. Parameter Estimation: Applications. Estimation of Dynamic Systems: Applications. Optimal Control and Estimation Theory. Appendices. Index.

Editorial Reviews

Praise for the First Edition
A nice feature of this book is that it makes the effort to explain the underlying principles behind the formula for each algorithm; the relationship between different algorithms is equally well addressed. … The text is a good combination of theory and practice. It will be a valuable addition to references for academic researchers and industrial engineers working in the field of estimation. It will also serve as a useful reference for graduate courses in control and estimation.
—AIAA Journal, Vol. 43, No. 1, January 2005

From the Publisher