Title :
An Alternative Look at the Constant-Gain Kalman Filter for State Estimation Over Erasure Channels
Author :
Silva, Eduardo I. ; Solis, Miguel A.
Author_Institution :
Dept. de Electron., Univ. Tec. Federico Santa Maria, Valparaiso, Chile
Abstract :
This technical note studies state estimation problems subject to data loss. We consider a class of switched estimators, where missing data is replaced by optimal estimates. The considered class of estimators encompasses a number of estimation schemes proposed in the literature. We show that the estimator that minimizes the steady-state estimation error covariance within that class, is given by a constant-gain Kalman filter which was previously proposed as an alternative to the Kalman filter with intermittent observations. As a by-product of our results, we derive expressions that allow one to compare, analytically, popular suboptimal data-dropout compensation mechanisms.
Keywords :
Kalman filters; channel estimation; linear systems; state estimation; LTI systems; constant-gain Kalman filter; data loss; erasure channels; linear time-invariant systems; state estimation problems; steady-state estimation error covariance; suboptimal data-dropout compensation mechanisms; switched estimators; Channel estimation; Covariance matrices; Kalman filters; Signal to noise ratio; State estimation; Steady-state; Data-dropouts; erasure channel; optimal estimation; signal-to-noise ratio (SNR) constraints; state estimation;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2013.2263647