MINIMAX STATE ESTIMATION FOR LINEAR STOCHASTIC SYSTEMS WITH NOISE UNCERTAINTY.

H. Vincent Poor, Douglas P. Looze

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

The problem of minimax linear state estimation for linear stochastic systems driven and observed in noises whose second-order properties are unknown is considered. Two general aspects of this problem are treated: the one-dimensional problem with uncertain noise spectra and the multidimensional problem with uncertain componentwise noise correlation. General minimax results are presented for each of these situations involving characterizations of the minimax filters in terms of least-favorable second-order properties. Explicit solutions are given for the spectral-band uncertainty model in the one-dimensional cases treated and for a matrix-norm neighborhood model in the multidimensional case.

Original languageEnglish (US)
Pages (from-to)1020-1025
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume2
StatePublished - Jan 1 1980
EventUnknown conference - Albuquerque, NM
Duration: Dec 10 1980Dec 12 1980

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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