Gaussian smoothers for nonlinear systems with one-step randomly delayed measurements

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Abstract

This technical note is concerned with the nonlinear state smoothing problem in the case that the measurements are randomly delayed by one sampling time. Under Gaussian domain, two general Gaussian approximation (GA) and Gaussian mixture approximation (GMA) smoothers are proposed in minimum mean square error (MMSE) sense. The smoothing implementation is transformed into computing some special posterior covariances, which triggers the development of the new unscented Kalman smoother (UKS) by applying unscented transformation (UT). Simulation results demonstrate the superior performance of the proposed GA-UKS and GMA-UKS algorithms.

Original languageEnglish
Article number6403515
Pages (from-to)1828-1835
Number of pages8
JournalIEEE Transactions on Automatic Control
Volume58
Issue number7
DOIs
StatePublished - 2013

Keywords

  • Gaussian approximation
  • Gaussian mixture approximation
  • nonlinear state
  • one-step randomly delayed measurement
  • smoother
  • unscented transformation

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