Title :
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
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;
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-1743-6
DOI :
10.1109/ICACI.2012.6463365
