An Introduction to Kalman Filtering with MATLAB Examples / by Narayan Kovvali, Mahesh Banavar, Andreas Spanias.

Format:

Book

Author/Creator:

Kovvali, Narayan., Author.

Banavar, Mahesh., Author.

Spanias, Andreas., Author.

Series:

Synthesis Lectures on Signal Processing, 1932-1694

Language:

English

Subjects (All):

Engineering.

Electrical engineering.

Signal processing.

Technology and Engineering.

Electrical and Electronic Engineering.

Signal, Speech and Image Processing .

Local Subjects:

Technology and Engineering.

Electrical and Electronic Engineering.

Signal, Speech and Image Processing .

Physical Description:

1 online resource (IX, 71 p.)

Edition:

1st ed. 2014.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2014.

Summary:

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.

Contents:

Acknowledgments

Introduction

The Estimation Problem

The Kalman Filter

Extended and Decentralized Kalman Filtering

Conclusion

Notation

Bibliography

Authors' Biographies.

ISBN:

9783031025365

3031025369