AN ADAPTIVE ROBUSTIZING APPROACH TO KALMAN FILTERING

被引：0
|
作者：
KOVACEVIC, BD
DUROVIC, ZM
机构：
来源：
CONTROL AND COMPUTERS | 1994年 / 22卷 / 01期
关键词：
KALMAN FILTERS; ROBUST FILTERING ADAPTIVE SYSTEMS; NONLINEAR FILTERS; NON-GAUSSIAN NOISE;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
`This paper considers the problem of robustifying the Kalman filter. Starting from the equivalence between the Kalman filter and the feast-squares regression problem, the authors propose a statistical approach called M-estimation to solve the regression problem robustly. In addition, robust M-estimators are derived for adaptive estimation of the unknown a priori state and observation noise statistics, simultaneously with the system state. The results of simulation demonstrating the robustness of the proposed estimators are also included.
引用
收藏
页码：7 / 11
页数：5
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