小波变换与卡尔曼滤波结合的RLG降噪方法

针对激光陀螺随机游走噪声其非平稳和非正态分布的特性,提出了基于小波变换的卡尔曼滤波的RLG降噪方法,该方法既具有小波变换对自相似过程的去相关作用和多分辨分析的功能,同时又保持了卡尔曼滤波器对未知信号的线性无偏最小方差估计的特点,实现了激光陀螺随机游走噪声的实时多尺度分解和最优估计。实测激光陀螺零偏信号去噪的结果表明,基于小波变换的卡尔曼滤波器使随机游走噪声的标准差降低了10.3%,降噪效果优于传统的卡尔曼滤波器。

Wavelet-based Kalman filtering for ring laser gyro denoising

According to the properties of non-stationary and non-normal distribution of random wandering drift in ring laser gyro (RLG), it is difficult to eliminate the noise by traditional method. A wavelet-based Kalman filter is employed based on conventional Kalman filtering. The method not only has the characters of multi-resolution analysis in wavelet domain and removing the properties of self-similarity, but also maintains linear unbiased and minimum error variance estimation of Kalman filtering for the unknown signal. Thus real-time multi-size decomposition and optimal estimation for random wandering noise can be realized. Practical measurement of RLG zero-biased signals after denoising show that standard error of random wandering drift has been reduced by 10.3% with wavelet-based Kalman filter. The denoising effect is better than traditional Kalman filter.