Optimal Estimation and Information Fusion: Theory and Algorithms

This book mainly focuses on the theme of optimizing estimation and sensor information fusion processing for stochastic dynamic systems. It summarizes the basic theories and methods of optimizing estimation and information fusion direction, including stochastic system models, optimal estimation methods, linear state estimation, nonlinear state estimation, information fusion models, structures, data processing methods, data association based on multi-source data estimation, and other aspects.

On the basis of years of teaching practice, the author optimizes the content layout, focuses on the basic theoretical methods of the subject, emphasizes the systematic nature of the theory and the rigor of expression, selectively cuts out some outdated content, and introduces some important and widely accepted new developments in the subject.

On the other hand, this book also serves as a reference material for technical developers in this field.