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  1. 2009.06.15 kalman filter

kalman filter

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An Introduction to the Kalman Filter
Greg Welch
1
and Gary Bishop
2
TR 95-041
Department of Computer Science
University of North Carolina at Chapel Hill
Chapel Hill, NC 27599-3175
Updated: Monday, July 24, 2006
Abstract
In 1960, R.E. Kalman published his famous paper describing a recursive solution
to the discrete-data linear filtering problem. Since that time, due in large part to advances
in digital computing, the Kalman filter has been the subject of extensive research
and application, particularly in the area of autonomous or assisted
navigation.
The Kalman filter is a set of mathematical equations that provides an efficient computational
(recursive) means to estimate the state of a process, in a way that minimizes
the mean of the squared error. The filter is very powerful in several aspects:
it supports estimations of past, present, and even future states, and it can do so even
when the precise nature of the modeled system is unknown.
The purpose of this paper is to provide a practical introduction to the discrete Kalman
filter. This introduction includes a description and some discussion of the basic
discrete Kalman filter, a derivation, description and some discussion of the extended
Kalman filter, and a relatively simple (tangible) example with real numbers &
results.
1.
welch@cs.unc.edu, http://www.cs.unc.edu/~welch
2.
gb@cs.unc.edu, http://www.cs.unc.edu/~gb


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