Please note: In order to keep Hive up to date and provide users with the best features, we are no longer able to fully support Internet Explorer. The site is still available to you, however some sections of the site may appear broken. We would encourage you to move to a more modern browser like Firefox, Edge or Chrome in order to experience the site fully.

An Introduction to Kalman Filtering with MATLAB Examples, PDF eBook

An Introduction to Kalman Filtering with MATLAB Examples PDF

Part of the Synthesis Lectures on Signal Processing series

PDF

Please note: eBooks can only be purchased with a UK issued credit card and all our eBooks (ePub and PDF) are DRM protected.

Description

The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian.

Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications, e.g., target tracking, guidance and navigation, and communications systems.

The purpose of this book is to present a brief introduction to Kalman filtering.

The theoretical framework of the Kalman filter is first presented, followed by examples showing its use in practical applications.

Extensions of the method to nonlinear problems and distributed applications are discussed.

A software implementation of the algorithm in the MATLAB programming language is provided, as well as MATLAB code for several example applications discussed in the manuscript.

Information

Other Formats

Information

Also in the Synthesis Lectures on Signal Processing series