Stability in linear estimation

Author

Kelly, Patrick A. ; Root, William L.

Author_Institution

Dept. of Electr. & Comput. Eng., Massachusetts Univ., Amherst, MA, USA

Volume

38

Issue

1

fYear

1992

fDate

1/1/1992 12:00:00 AM

Firstpage

39

Lastpage

49

Abstract

The stability with respect to model uncertainty of linear estimators of the coefficients of a linear combination of deterministic signals in noise is investigated. A class of estimators having nominal performances constrained to be close to that of the nominal linear, unbiased, minimum-variance (LUMV) estimator is specified. Two estimator stability indexes are defined, one based on a worst-case estimate mean-square error and the other on a type of signal-to-noise ratio. The estimator minimizing each index, subject to the optimality constraints, is found by reference to related LUMV estimation results. In most cases, the minimizing (or most stable) estimator is the same under the two indexes

Keywords

estimation theory; signal processing; stability criteria; LUMV estimation; deterministic signals; estimator stability indexes; linear estimation; linear unbiased minimum variance estimator; model uncertainty; noise; optimality constraints; signal-to-noise ratio; stability; worst-case estimate mean-square error; Communication system control; Helium; Hilbert space; Life estimation; Noise robustness; Random variables; Robust stability; Signal processing; Signal to noise ratio; Uncertainty;

fLanguage

English

Journal_Title

Information Theory, IEEE Transactions on

Publisher

ieee

ISSN

0018-9448

Type

jour

DOI

10.1109/18.108247

Filename

108247