An improved Sage-Husa adaptive filtering algorithm

Author

Zheng, Zhu ; Shirong, Liu ; Botao, Zhang

Author_Institution

Inst. of Autom., Hangzhou Dianzi Univ., Hangzhou, China

fYear

2012

fDate

25-27 July 2012

Firstpage

5113

Lastpage

5117

Abstract

In order to meet the requirement of precision and stability, a new method is proposed which uses fading factor and innovation threshold to estimate noise covariance matrix and modify the observation error covariance matrix dynamically. This algorithm was used to the GPS/INS integrated navigation system and compared with the simplified Sage-Husa filtering. The simulation results show that the improved Sage-Husa self-adaptive filtering algorithm, which makes the process better both in the precision and stability, is superior to the simplified Sage-Husa filtering.

Keywords

Global Positioning System; adaptive filters; covariance matrices; filtering theory; inertial navigation; GPS-INS integrated navigation system; Sage-Husa adaptive filtering algorithm; fading factor; global positioning system; inertial navigation system; innovation threshold; noise covariance matrix estimation; observation error covariance matrix modification; Adaptive filters; Electronic mail; Global Positioning System; Heuristic algorithms; Kalman filters; Sage-Husa adaptive filtering; fading factor; innovation threshold; integrated navigation;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (CCC), 2012 31st Chinese

Conference_Location

Hefei

ISSN

1934-1768

Print_ISBN

978-1-4673-2581-3

Type

conf

Filename

6390828