MATLAB and Simulink Based Books

bayesian estimation and tracking

Bayesian Estimation and Tracking: A Practical Guide

Written for graduate-level courses on estimation and tracking methods, this book provides a comprehensive overview of methods for estimating both linear and nonlinear dynamic systems driven by Gaussian and non-Gaussian noises. The book provides detailed derivations of each tracking algorithm as well as illustrative and detailed step-by-step instructions and block diagrams of the algorithm process flow that make coding of each tracking filter simple and easy. Topics include linear Kalman filters, extended and finite-difference Kalman filters, and sigma-point Kalman filters (unscented, spherical simplex, and Gauss-Hermite).

MATLAB is used to solve numerous examples in the book.

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About This Book

Anton J. Haug, Johns Hopkins University

John Wiley & Sons, Inc., 2012

ISBN: 978-0-470-62170-7
Language: English