THE ITERATED KALMAN FILTER UPDATE AS A GAUSS-NEWTON METHOD

被引：334

作者：

BELL, BM ^{[1
]}

CATHEY, FW ^{[1
]}

机构：

[1] BOEING DEF & SPACE GRP,AVION TECHNOL,SEATTLE,WA 98124

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 1993年 / 38卷 / 02期

关键词：

D O I：

10.1109/9.250476

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We show that the iterated Kalman filter (IKF) update is an application of the Gauss-Newton method for approximating a maximum likelihood estimate. We also present an example in which the iterated Kalman filter update and maximum likelihood estimate show correct convergence behavior as the observation becomes more accurate, whereas the extended Kalman filter update does not.

引用

页码：294 / 297

页数：4