STABILITY IN LINEAR-ESTIMATION

被引：0
|
作者：
KELLY, PA
ROOT, WL
机构：
[1] UNIV MICHIGAN,DEPT ELECT ENGN & COMP SCI,ANN ARBOR,MI 48109
[2] UNIV MICHIGAN,DEPT AEROSP ENGN,ANN ARBOR,MI 48109
来源：
IEEE TRANSACTIONS ON INFORMATION THEORY | 1992年 / 38卷 / 01期
基金：
美国国家科学基金会;
关键词：
LINEAR UNBIASED MINIMUM-VARIANCE ESTIMATION; MODEL UNCERTAINTY; STABILITY;
D O I：
10.1109/18.108247
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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 (o 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.
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页码：39 / 49
页数：11
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