An alternative look at the constant-gain kalman filter for state estimation over erasure channels

Eduardo I. Silva, Miguel A. Solis

Research output: Contribution to journalArticlepeer-review

45 Citations (Scopus)

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.

Original languageEnglish
Article number6517257
Pages (from-to)3259-3265
Number of pages7
JournalIEEE Transactions on Automatic Control
Volume58
Issue number12
DOIs
Publication statusPublished - 1 Dec 2013
Externally publishedYes

Keywords

  • Data-dropouts
  • Erasure channel
  • Optimal estimation
  • Signal-to-noise ratio (SNR) constraints
  • State estimation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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