A hybrid wavelet-Kalman filter method for FOG random noise

被引：0
|
作者：
Chen, Chunzhou [1 ]
Zhang, Xiaoli [1 ]
Peng, Xiafu [1 ]
Yang, Gongliu [2 ]
机构：
[1] Xiamen Univ, Dept Automat, Xiamen, Peoples R China
[2] Beihang Univ, Dept Optoelect Engn, Beijing, Peoples R China
来源：
2019 CHINESE AUTOMATION CONGRESS (CAC2019) | 2019年
关键词：
fiber optic gyro; AR model; recursive least squares; wavelet threshold filtering; Kalman filtering;
D O I：
10.1109/cac48633.2019.8996702
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a hybrid wavelet-Kalman filter method to suppress the fiber optic gyro (FOG) random noise which can potentially reduce the accuracy of inertial navigation system. Our approach starts with wavelet threshold filtering for FOG signal preprocess, and post-processes the wavelet-reconstructed signal using Kalman filtering based on improved AR model. The proposed method can not only analyze the signal with multi-resolution, but also estimate the signal optimally. We validate the performance of the proposed method in simulation experiments and compare against wavelet threshold filtering.
引用
收藏
页码：2405 / 2410
页数：6
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