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- 2012-11-26
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Description: Kalman filter algorithm implemented in C
Optimal linear filtering theory originated in the 1940s, American scientists Wiener and the former Soviet Union scientists Kолмогоров research, and their descendants are collectively referred to as Wiener filtering theory. In theory, the biggest drawback of the Wiener filter is needed for unlimited data, does not apply to real-time processing. To overcome this shortcoming, in the 1960s, Kalman state space model of the introduction of filtering theory, and a recursive estimation algorithm is derived, later known as the Kalman filter theory. Kalman filter based on minimum mean square error of the estimated best practices, to seek a recursive estimation algorithm, the basic idea is: the state space model of signal and noise, the first time to estimate and the present moment the observed values to update the estimated state variables, find the estimated value of the moment. It is suitable for real-time processing and computing.
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