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The Kalman filter is a set of mathematical equations that provides an efficient computational (recursive) solution of the least-squares method.
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"The Kalman filter is a set of mathematical equations that provides an efficient computational (recursive) solution of the least-squares method. 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." (quoted from [02])

This version of the Kalman filter is in fact a Variable-Dimension Extended Kalman Filter (VDEKF). It supports optimized algorithms (translated from Fortran - see [01]), even in the presence of correlated process or measurement noise.

For a usage example, please check out the example page in the related pages section.

**References**- [01] Bierman, G. J. "Factorization Methods for Discrete Sequential
Estimation", Academic Press, 1977.

[02] Welch, G. and Bishop, G. "An Introduction to the Kalman Filter", http://www.cs.unc.edu/~welch/kalman/kalmanIntro.html

kfilter

Author(s): Vincent Zalzal, Sylvain Marleau, Richard Gourdeau

autogenerated on Wed Jul 23 04:33:42 2014

Author(s): Vincent Zalzal, Sylvain Marleau, Richard Gourdeau

autogenerated on Wed Jul 23 04:33:42 2014