Robust estimation with unknown noise statistics

被引：127

作者：

Durovic, ZM ^{[1
]}

Kovacevic, BD ^{[1
]}

机构：

[1] Univ Belgrade, Fac Elect Engn, YU-11000 Belgrade, Yugoslavia

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 1999年 / 44卷 / 06期

关键词：

adaptive filtering; non-Gaussian noise; robust estimation;

D O I：

10.1109/9.769393

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 equivalence between the Kalman filter and a particular least squares regression problem is established and the regression problem is sol, ed robustly using a statistical approach named M-estimation, M-robust estimators are derived for adaptive estimation of the unknown a priori state and observation noise statistics simultaneously with the system states. The feasibility of the approach is demonstrated with simulation.

引用

页码：1292 / 1296

页数：5

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