A study on identification and suppressing algorithm of FOG´s random noise

Author

Hui Yuan ; Zhaohui Liu ; Dongsheng Liang ; Kai Cui

Author_Institution

Dept. of Opt. Eng., Grad. Univ. of Chinese Acad. of Sci., Xi´´an, China

fYear

2012

fDate

18-20 Oct. 2012

Firstpage

1195

Lastpage

1199

Abstract

In this paper, the Allan variance technique is used in analyzing the output signal of a fiber optic gyroscope, by which the characteristics of the noise terms in the angular velocity data was determined. Then we process the random drift data of the FOG with a Kalman Filter based on the theory of time series analysis. On the other hand, an LMS adaptive filter is also applied to the random drift data. Comparative analysis on the filtering effect and their advantages and disadvantages of both algorithms is carried out. The results show both algorithms has a certain role on suppressing the random drift of the gyroscope, and the LMS adaptive filter is more effective and has a better adaptability in practice.

Keywords

Kalman filters; adaptive filters; fibre optic gyroscopes; interference suppression; optical fibre filters; random noise; signal processing; time series; Allan variance technique; FOG random noise; Kalman filter; LMS adaptive filter; angular velocity data; fiber optic gyroscope; gyroscope random drift data; identification algorithm; noise terms characteristics; output signal analysis; random drift suppression; time series analysis; Adaptive filters; Filtering algorithms; Finite impulse response filter; Kalman filters; Least squares approximation; Noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4673-1743-6

Type

conf

DOI

10.1109/ICACI.2012.6463365

Filename

6463365