Kalman滤波代码

% Version 1.0, June 30, 2004 % % This tutorial function was written by Michael C. Kleder % % INTRODUCTION % % Many people have heard of Kalman filtering, but regard the topic % as mysterious. While it's true that deriving the Kalman filter and % proving mathematically that it is "optimal" under a variety of % circumstances can be rather intense, applying the filter to % a basic linear system is actually very easy. This Matlab file is % intended to demonstrate that. % % An excellent paper on Kalman filtering at the introductory level, % without detailing the mathematical underpinnings, is: % "An Introduction to the Kalman Filter" % Greg Welch and Gary Bishop, University of North Carolina % http://www.cs.unc.edu/~welch/kalman/kalmanIntro.html % % PURPOSE: % % The purpose of each iteration of a Kalman filter is to update % the estimate of the state vector of a system (and the covariance % of that vector) based upon the information in a new observation. % The version of the Kalman filter in this function assumes that % observations occur at fixed discrete time intervals. Also, this % function assumes a linear system, meaning that the time evolution % of the state vector can be calculated by means of a state transition % matrix.