An Introduction to Kalman Filtering with MATLAB Examples (Synthesis Lectures on Signal Processing)

by Narayan Kovvali, Mahesh Banavar, and Andreas Spanias

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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.
  • ISBN13 9781627051392
  • Publish Date 1 September 2013
  • Publish Status Unknown
  • Publish Country US
  • Publisher Morgan & Claypool Publishers
  • Imprint Morgan and Claypool Life Sciences
  • Format Paperback
  • Pages 81
  • Language English