基于小波域极大似然方法的光纤陀螺随机噪声参数估计

Parameter Estimation for Stochastic Noises in Fiber Optical Gyro Based on Maximum Likelihood Estimation in Wavelet Domain

光纤陀螺随机噪声主要包括1/fγ分形噪声和白噪声,估计光纤陀螺随机噪声的参数就是估计分形噪声的强度、白噪声的强度以及分形参数。由于分形噪声在小波变换域的特殊性质,在小波变换域处理分形噪声比较方便;同时极大似然参数估计方法是一种鲁棒性很强的方法,因此本文采用小波变换域极大似然估计方法估计光纤陀螺随机噪声的参数。通过仿真对算法进行了检验,证明了这种方法用于光纤陀螺随机噪声参数估计的有效性。

Stochastic noises in FOG mainly consist of fractal (1/fγ) noises and white noises,and the problem of estimating parameters of stochastic noises in FOG is to estimate fractal noise level,white noise level and fractal parameter.For fractal noise's special property in wavelet domain,it is convenient to deal with fractal noise;furthermore,maximum likelihood parameter estimation method is a rather robust method,in the paper,maximum likelihood method in wavelet domain is employed to estimate parameters of stochastic noises in FOG.Simulation results show that maximum likelihood estimation algorithm is efficient to estimate parameters of stochastic noises in FOG.