Impact of correlation errors on the optimum Kalman filter gain identification in a single sensor environment

Abstract

The impact of errors in the innovation correlation functions evaluation, related to the suboptimal filter, on the identification of the optimum steady state Kalman filter gains are investigated. This issue arises in all real time applications, where the correlations must be calculated from experimental data. An identification algorithm proposed in the… (More)

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