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
收藏
页码：1292 / 1296
页数：5
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