📄 the kalman filter.htm
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Center</A>.
<LI>On November 16, 2005, Kalman was awarded Columbia Engineering
School Alumni Association抯 <B>Egleston Medal</B> for <I>Distinguished
Engineering Achievement</I>. See <A
href="http://www.columbia.edu/cu/news/05/11/elgeston_medal.html">online
article</A> or <A
href="http://www.cs.unc.edu/~welch/kalman/media/pdf/Egelston_Medal_20051116.pdf">local
copy</A>.
<LI>On February 19, 2008, Kalman will be awared the <A
href="http://www.nae.edu/nae/awardscom.nsf/weblinks/NAEW-4NHML8?OpenDocument">Charles
Stark Draper Prize</A> for "the development and dissemination of the
optimal digital technique (known as the Kalman Filter) that is
pervasively used to control a vast array of consumer, health,
commercial and defense products." More information is <A
href="http://www8.nationalacademies.org/onpinews/newsitem.aspx?RecordID=01022008">available
here</A>. (See also this <A
href="http://www.cs.unc.edu/~welch/kalman/media/pdf/Kalman_Draper_2008.pdf">archived
copy of the press release</A>.) </LI></UL>
<LI><A href="http://www.cs.unc.edu/~welch/kalman/kalmanPaper.html">His
seminal (1960) paper</A>. </LI></UL></TD></TR></TBODY></TABLE><A
name=Anchor-48213></A>
<TABLE cellSpacing=4 cellPadding=0 border=0>
<TBODY>
<TR>
<TD vAlign=top width=84><IMG height=68
src="The Kalman Filter.files/kf_book.gif" width=84 align=top border=0></TD>
<TD vAlign=center>
<H2>Printed Reference Material</H2></TD></TR>
<TR>
<TD vAlign=top colSpan=2>
<UL>
<LI>For beginners, we highly recommend reading <A
href="http://www.cs.unc.edu/~welch/kalman/maybeck.html">Chapter 1 of
this book</A> by <A href="http://en.afit.edu/maybeck/">Peter S.
Maybeck</A> on the subjects of stochastic models, estimation, and
control. Although the remaining chapters may appear daunting, the book
is thorough and complete.
<LI>For a somewhat more advanced presentation, we have written "<A
href="http://www.cs.unc.edu/~welch/kalman/kalmanIntro.html">An
Introduction to the Kalman Filter</A>" (also <A
href="http://yaoxuchen.googlepages.com/kalman">available in Chinese</A>)
and a more substantial <A
href="http://www.cs.unc.edu/~tracker/media/pdf/SIGGRAPH2001_CoursePack_08.pdf">course
pack (booklet)</A> for our <A
href="http://www.cs.unc.edu/~tracker/ref/s2001/kalman/index.html">tutorial
on the Kalman filter</A> presented at <A
href="http://www.siggraph.org/s2001/">ACM SIGGRAPH 2001</A>. (Please
read the <A href="http://info.acm.org/pubs/toc/CRnotice.html">ACM
Copyright Notice</A> for the latter.)
<LI>In addition, here are several other <A
href="http://www.cs.unc.edu/~welch/kalman/kalmanBooks.html">Kalman
filter books</A>, and several of the sites below provide reading lists.
<LI>Kalman's <A
href="http://www.cs.unc.edu/~welch/kalman/kalmanPaper.html">seminal
paper (1960)</A>.
<LI>Sorenson's <A
href="http://www.cs.unc.edu/~welch/kalman/sorensonPaper.html">"Gauss to
Kalman" article (1970)</A>. </LI></UL></TD></TR></TBODY></TABLE><A
name=Anchor-49575></A>
<TABLE cellSpacing=4 cellPadding=0 border=0>
<TBODY>
<TR>
<TD vAlign=top width=84><A
href="http://www.cs.unc.edu/~tracker/ref/s2001/kalman/index.html"><IMG
height=80 src="The Kalman Filter.files/kf_class.gif" width=84
border=0></A></TD>
<TD vAlign=center>
<H2><A name=Anchor-Courses-49575></A>Courses</H2></TD></TR>
<TR>
<TD vAlign=top colSpan=2>
<UL>
<LI>January 19-23, 2009, Fullerton, California, USA
<UL>
<LI>"<A href="http://kalmanfilteringgpsins.com/register">Application
of Kalman Filtering to GPS, INS, & Navigation</A>"<BR><A
href="http://www.ecs.fullerton.edu/~mgrewal/">Dr. M. S. Grewal</A>,
California State University, Fullerton </LI></UL>
<LI>At <A href="http://www.siggraph.org/s2001/">ACM SIGGRAPH 2001</A> we
presented a <A
href="http://www.cs.unc.edu/~tracker/ref/s2001/kalman/index.html">tutorial
on the Kalman filter</A>. (Please read the <A
href="http://info.acm.org/pubs/toc/CRnotice.html">ACM Copyright
Notice</A>.) </LI></UL>
<UL></UL></TD></TR>
<TR>
<TD vAlign=top></TD>
<TD vAlign=top></TD></TR></TBODY></TABLE><A name=Anchor-37516></A>
<TABLE cellSpacing=4 cellPadding=0 border=0>
<TBODY>
<TR>
<TD vAlign=top width=84><IMG height=84
src="The Kalman Filter.files/kf_www.gif" width=84 border=0></TD>
<TD vAlign=center>
<H2>Other Sites and Electronic Reference</H2></TD></TR>
<TR>
<TD vAlign=top colSpan=2>
<H4>Local Material</H4>
<UL>
<LI>"<A href="http://www.cs.unc.edu/~welch/kalman/kalmanIntro.html">An
Introduction to the Kalman Filter</A>" by <A
href="http://www.cs.unc.edu/~welch">Greg Welch</A> and <A
href="http://www.cs.unc.edu/~gb">Gary Bishop</A>. The article has also
been <A href="http://yaoxuchen.googlepages.com/kalman">translated into
Chinese</A> by Xuchen Yao, a student at Institute of Acoustics, the <A
href="http://english.cas.ac.cn/Eng2003/page/home.asp">Chinese Academy of
Sciences</A> (January, 2007. See also the <A
href="http://www.cs.unc.edu/~welch/kalman/media/pdf/kalman_intro_chinese.pdf">local
archived copy</A>.).
<LI>Course notes from our <A
href="http://www.cs.unc.edu/~tracker/ref/s2001/kalman/index.html">tutorial
on the Kalman filter</A> presented at <A
href="http://www.siggraph.org/s2001/">ACM SIGGRAPH 2001</A>. (Please
read the <A href="http://info.acm.org/pubs/toc/CRnotice.html">ACM
Copyright Notice</A>.)
<LI><A
href="http://www.cs.unc.edu/~welch/media/pdf/kalmanIntroSlides.pdf">Slides</A>
from an older introductory talk by <A
href="http://www.cs.unc.edu/~welch">Greg Welch</A> and <A
href="http://www.cs.unc.edu/~gb">Gary Bishop</A>.
<LI>Our very own Java-based <A
href="http://www.cs.unc.edu/~welch/kalman/kftool/index.html">Kalman
Filter Learning Tool</A>. </LI></UL>
<H4>External Material</H4>
<UL>
<LI><A href="http://www.wikipedia.org/">Wikipedia</A> has an <A
href="http://en.wikipedia.org/wiki/Kalman_filter">excellent article on
the Kalman filter</A>.
<LI>In a 1997 Innovation column of <A
href="http://www.gpsworld.com/">GPS World</A>, Larry J. Levy wrote a
very nice introduction to the Kalman filter titled "<A
href="http://www.cs.unc.edu/~welch/kalman/Levy1997/index.html">The
Kalman Filter: Navigation's Integration Workhorse</A>." (Also available
as <A
href="http://www.cs.unc.edu/~welch/kalman/Levy1997/Levy1997_KFWorkhorse.pdf">PDF
file</A>.) Levy provides some historical perspective, a non-mathematical
explanation, and of course a mathematical explanation with examples.
<LI><A href="http://www.ai.mit.edu/~murphyk/">Kevin Murphy</A>, a
postdoc in the <A href="http://www.ai.mit.edu/">MIT AI Lab</A>, has a
nice <A
href="http://www.ai.mit.edu/~murphyk/Software/Kalman/kalman.html">Kalman
filter web page</A>. There he provides <A
href="http://www.ai.mit.edu/~murphyk/Software/Kalman/kalman_download.html">several
MatLab toolboxes</A>, including a Kalman filter toolbox. (<A
href="http://www.mathworks.com/products/prodoverview.shtml">MatLab</A>
is a product of <A href="http://www.mathworks.com/">The MathWorks</A>.)
<LI><A href="http://www.cse.ogi.edu/~rudmerwe/">Rudolph van der
Merwe</A> maintains a very nice web site on signal processing research
including work on <A
href="http://cslu.cse.ogi.edu/nsel/research/ukf.html">Unscented Kalman
Filters</A>. (The idea for the UKF was originally introduced by Simon
Julier and Jeff Uhlmann.) Their site contains papers and a <A
href="http://choosh.csee.ogi.edu/rebel/">MatLab toolkit called ReBEL</A>
which contains functions and scripts for the Kalman filter, particle
filters (in general), and the Unscented Kalman Filter. (<A
href="http://www.mathworks.com/products/prodoverview.shtml">MatLab</A>
is a product of <A href="http://www.mathworks.com/">The MathWorks</A>.)
<A href="http://cslu.cse.ogi.edu/publications/ps/UPF_CSLU_talk.pdf">Here
are the slides</A> from a June 2002 talk Rudolph gave at a <A
href="http://cslu.cse.ogi.edu/">CSLU</A> weekly seminar.
<LI>"<A
href="http://www.cs.unc.edu/~welch/kalman/siam_cipra.html">Engineers
Look to Kalman Filtering for Guidance</A>," an article by Barry Cipra,
SIAM News, Vol. 26, No. 5, August 1993.
<LI><A
href="http://www.innovatia.com/software/papers/kalman.htm">Innovatia
Software's Kalman Filtering Page</A>, provided by <A
href="mailto:dansimon@innovatia.com">Dr. Dan Simon</A>.
<LI><A href="http://home%20.earthlink.net/~pdjoseph">Peter D. Joseph's
Home Page</A> containing material on Kalman filters.
<LI>Intel's <A
href="http://www.intel.com/research/mrl/research/opencv/index.htm">OpenCV</A>
Reference Manual includes some introductory Kalman filter prose and
library functions.
<DIV></DIV>
<LI><A href="http://r.w.r.darling.googlepages.com/">R. W. R. Darling</A>
has a very nice online survey of nonlinear filtering. (The <A
href="http://www.nonlinearfiltering.webhop.net/">original site</A> does
not seem to work any more, but the survey <A
href="http://web.archive.org/web/20080214024542/http://www.nonlinearfiltering.webhop.net/">is
accessible via "The Wayback Machine"</A>.)
<LI><A href="http://www.omatrix.com/contact.html">Harmonic Software</A>
sells a <A href="http://www.omatrix.com/kbf.html">Kalman Filter
Interface Pack (KBF)</A> for their <A
href="http://www.omatrix.com/">O-Matrix</A> product. KBF is a GUI-based
environment for graphically designing, building, and analyzing Kalman
filters using the Kalman filter functions available in O-Matrix.
<LI>Jean-Philippe Drecourt, a PhD student working on the <A
href="http://projects.dhi.dk/daihm/">DHI Data Assimilation in
Hydrological and Hydrodynamic Models site</A> project, wrote a <A
href="http://projects.dhi.dk/daihm/Files/KFlitreview.pdf">literature
review on Kalman filtering</A> with references to hydrological
modelling. He reviews the Kalman filter itself, and some of the most
important suboptimal schemes.
<LI>Andre Adrian, a Senior Engineer at <A
href="http://www.dfs.de/dfs/internet/english/index.html">DFS in
Germany</A>, used the Kalman filter (and variations) to create a central
tracker for the german air traffic control. He has provided <A
href="http://www.andreadrian.de/kalman_filter/">a few articles here</A>.
<LI><A href="mailto:rrrb@sureste.com">Ruben R. Raygosa</A> has
contributed a <A
href="http://www.cs.unc.edu/~welch/kalman/media/misc/RAYGOSA_KF_tutorial.zip">Spanish
tutorial for the Kalman filter</A>.
<LI>Vladimir Tislenko <A
href="http://www.cs.unc.edu/~welch/kalman/tislenko.html">wrote to tell
us about two Kalman rivers connected to the Irtysh river in Siberia</A>.
</LI></UL></TD></TR></TBODY></TABLE><A name=Anchor-23522></A>
<TABLE cellSpacing=4 cellPadding=0 border=0>
<TBODY>
<TR>
<TD vAlign=top width=84><IMG height=84
src="The Kalman Filter.files/kf_drive.gif" width=84 border=0></TD>
<TD vAlign=center>
<H2>Software</H2></TD></TR>
<TR>
<TD vAlign=top colSpan=2>
<UL>
<LI>A <A
href="http://www.cs.unc.edu/~welch/kalman/media/misc/kftool_matlab.zip">zip
file</A> of some MatLab source code for a prototype of our Java-based <A
href="http://www.cs.unc.edu/~welch/kalman/kftool/index.html">Kalman
Filter Learning Tool.</A>
<LI><A href="http://sourceforge.net/projects/opencvlibrary/">OpenCV</A>
includes some Kalman Filter functions, and the Reference Manual includes
some introductory prose. (The prose is quite similar to our <A
href="http://www.cs.unc.edu/~welch/kalman/kalmanIntro.html">introductory
paper</A>.) The entire library can be <A
href="http://sourceforge.net/projects/opencvlibrary/">downloaded</A>
after agreeing to their <A
href="http://www.intel.com/research/mrl/research/opencv/license.htm">license</A>.
The Reference Manual is in the opencv-doc package.
<LI><A
href="http://www.acfr.usyd.edu.au/people/technical/mstevens/">Michael
Stevens</A> (a Senior Research Engineer at the <A
href="http://www.acfr.usyd.edu.au/">Australian Centre for Field
Robotics</A>) has developed a nice <A
href="http://bayesclasses.sourceforge.net/Bayes++.html">library of C++
Bayesian Filtering Classes</A>. The classes represent and implement a
wide variety of numerical estimation algorithms for Bayesian/Kalman
Filtering. The classes provide tested and consistent numerical methods
and the class hierarchy explicitly represents the variety of filtering
algorithms and model types.
<LI><A href="http://www.cs.berkeley.edu/~murphyk/">Kevin Murphy</A> (see
above) provides <A
href="http://www.cs.berkeley.edu/~murphyk/Bayes/request.html">several
MatLab toolboxes</A>, including a Kalman filter toolbox. (<A
href="http://www.mathworks.com/products/prodoverview.shtml">MatLab</A>
is a product of <A href="http://www.mathworks.com/">The MathWorks</A>.)
<LI><SPAN class=ds2><A href="http://www.awblocker.com/">Alex Blocker</A>
at Boston University has developed and made available some Matlab tools
for Kalman filtering, smoothing, and estimation. (See <A
href="http://www.awblocker.com/">his web site</A> for notes,
instructions, and a link to the tools.) The tools are licensed under <A
href="http://www.gnu.org/licenses/lgpl.html">LGPL</A> 3.0. He says that
the learning algorithm he uses is similar to Kevin Murphy's, but is
extended to the case of a controlled system. He </SPAN><SPAN
class=ds2>includes a technical note on this algorithm and its
use.</SPAN>
<LI><A href="http://www.lce.hut.fi/~ssarkka/">Simo S鋜kk⌨️ 快捷键说明
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