Optimal Estimation of Dynamic Systems, Second Edition highlights the importance of both physical and numerical modeling in solving dynamics-based estimation problems found in engineering systems. Accessible to engineering students, applied mathematicians, and practicing engineers, the text presents the central concepts and methods of optimal estimation theory and applies the methods to problems with varying degrees of analytical and numerical difficulty. Different approaches are often compared to show their absolute and relative utility. The authors also offer prototype algorithms to stimulate the development and proper use of efficient computer programs. MATLAB® codes for the examples are available on the book’s website.
New to the Second Edition
With more than 100 pages of new material, this reorganized edition expands upon the best-selling original to include comprehensive developments and updates. It incorporates new theoretical results, an entirely new chapter on advanced sequential state estimation, and additional examples and exercises.
An ideal self-study guide for practicing engineers as well as senior undergraduate and beginning graduate students, the book introduces the fundamentals of estimation and helps newcomers to understand the relationships between the estimation and modeling of dynamical systems. It also illustrates the application of the theory to real-world situations, such as spacecraft attitude determination, GPS navigation, orbit determination, and aircraft tracking.
Least Squares Approximation
A Curve Fitting Example
Linear Batch Estimation
Linear Sequential Estimation
Nonlinear Least Squares Estimation
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
Appendix A: Review of Dynamical Systems
A Summary appears at the end of each chapter.
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