By Dan Simon - Optimal State Estimation: Kalman, H Infinity, and Nonlinear Appro (2006-07-08) [Hardcover]

by Dan Simon

A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering. While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed * Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimation * Simple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practice * MATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering. Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. A solutions manual is available for instructors. With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries. A solutions manual is available upon request from the Wiley editorial board.

Genres: Engineering, Mathematics, Science

Hardcover

First published January 1, 2006

Reviews

[Anas I.Abu-lehia · Rating 5 out of 5]

Probably, the best book explains estimation theory starting from the very basics needed foundations in maths and deep dig into Kalman filter; the most important algorithm of 20th century.
The mathematical derivation of formulas is very nice and simple, all detailed steps are listed, which makes reading it very easy without the need to revisit other resources, also very nice and exciting Appendices. Also, if you google the book, it has about 7000 citations.

[Guillermina · Rating 4 out of 5]

Very clearly written and well organized. I felt it had a special focus on how methods are related and derived. It is aimed at engineers and the methods are not presented from the statistical point of view, though.

[Kiet Huynh · Rating 5 out of 5]

More intuitive than Probabilistic Robotics

[Steve]

This book addresses Kalman filtering, and Peter Molenaar suggested it. It's cool -- I can (with the assistance of audio files from Molenaar's lectures on the text) actually understand this material, despite how dense and difficult would be otherwise.

Dan Simon seems very strange. Appendix C is about State Estimation and The Meaning of Life. In it, he talks about how he knows god exists and relates this to mathematics, but in such a superficial way that one can't take it seriously. There's essays on mathematics and Christianity on his web site.