An Introduction to Kalman Filtering with MATLAB Examples (Paperback)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Synthesis Lectures on Signal Processing
Release date:	October 2013
First published:	2014
Authors:	Narayan Kovvali • Mahesh Banavar • Andreas Spanias
Dimensions:	235 x 191mm (L x W)
Format:	Paperback
Pages:	71
ISBN-13:	978-3-03-101408-6
Languages:	English
Subtitles:	English
Categories:	Books > Professional & Technical > Technology: general issues > Engineering: general Books > Professional & Technical > Energy technology & engineering > Electrical engineering > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	3-03-101408-1
Barcode:	9783031014086

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