A reduced-order model for integrated GPS/INS

被引：12

作者：

He, XF ^{[1
]}

Chen, YQ ^{[1
]}

Iz, HB ^{[1
]}

机构：

[1] Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Kowloon, Hong Kong

来源：

IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE | 1998年 / 13卷 / 03期

关键词：

D O I：

10.1109/62.659864

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

The dominant factor in determining the computation time of the Kalman filter is the dimension n of the model state vector. The number of computations per iteration is on the order of n(3). Any reduction in the number of states will benefit directly in terms of increased computation time. In this paper, a high order model in integrated GPS/INS is described first, then a reduced-order model based on the high-order model, is developed. Finally, a faster tracking approach for Kalman filters is discussed. A typical aircraft trajectory is designed for a complex high-dynamic aircraft flight experiment. A Monte Carlo analysis shows that the reduced order model presented in this paper provides satisfactory accuracy for aircraft navigation.

引用

页码：40 / 45

页数：6