MINIMAX STATE ESTIMATION FOR LINEAR STOCHASTIC SYSTEMS WITH NOISE UNCERTAINTY.

H. Vincent Poor; Douglas P. Looze

doi:10.1109/cdc.1980.271956

MINIMAX STATE ESTIMATION FOR LINEAR STOCHASTIC SYSTEMS WITH NOISE UNCERTAINTY.

H. Vincent Poor, Douglas P. Looze

Research output: Contribution to journal › Conference article › peer-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 language	English (US)
Pages (from-to)	1020-1025
Number of pages	6
Journal	Proceedings of the IEEE Conference on Decision and Control
Volume	2
DOIs	https://doi.org/10.1109/cdc.1980.271956
State	Published - 1980
Event	Unknown conference - Albuquerque, NM Duration: Dec 10 1980 → Dec 12 1980

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

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10.1109/cdc.1980.271956

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title = "MINIMAX STATE ESTIMATION FOR LINEAR STOCHASTIC SYSTEMS WITH NOISE UNCERTAINTY.",

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.",

author = "Poor, {H. Vincent} and Looze, {Douglas P.}",

year = "1980",

doi = "10.1109/cdc.1980.271956",

language = "English (US)",

volume = "2",

pages = "1020--1025",

journal = "Proceedings of the IEEE Conference on Decision and Control",

issn = "0191-2216",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Unknown conference ; Conference date: 10-12-1980 Through 12-12-1980",

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T1 - MINIMAX STATE ESTIMATION FOR LINEAR STOCHASTIC SYSTEMS WITH NOISE UNCERTAINTY.

AU - Poor, H. Vincent

AU - Looze, Douglas P.

PY - 1980

Y1 - 1980

N2 - 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.

AB - 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.

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DO - 10.1109/cdc.1980.271956

M3 - Conference article

AN - SCOPUS:0019244719

SN - 0191-2216

VL - 2

SP - 1020

EP - 1025

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

T2 - Unknown conference

Y2 - 10 December 1980 through 12 December 1980

ER -

MINIMAX STATE ESTIMATION FOR LINEAR STOCHASTIC SYSTEMS WITH NOISE UNCERTAINTY.

Abstract

All Science Journal Classification (ASJC) codes

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