光纤陀螺自适应阈值滤波新方法

New Adaptive Threshold Filtering for Fiber Optic Gyroscopes

通过Lipschitz指数分析不同分解尺度上信号与噪声对应的小波系数变化情况和光纤陀螺输出信号模型,研究了一种新的基于离散小波变换的自适应滤波方法.该方法可根据光纤陀螺输出信号的能级自动调整小波系数在不同尺度上的阈值.构造了一种新的阈值函数,用一个多项式来削弱低于阈值的小波系数,能最大限度地保留真实信息.与软硬阈值函数相比,对于不同信噪比的信号均表现出较好的性能.仿真实验表明,与传统固定阈值滤波相比,新算法能更好地去除噪声,改进光纤陀螺的零偏稳定性和随机游走等技术指标.

Through Lipschitz index analyzsis of changes in wavelet factor of the signal and noise in different discrete scales, the signal model of fiber optic gyroscope （FOG） is established. Based on the discrete wavelet transform, a new adaptive filtering algorithm is studied. This algorithm can automatically adjust the threshold values of the wavelet coefficients at different scales in accordance with the energy level of FOG＇s output signal. Thus, a new threshold function is obtained, which weakens wavelet coefficients lower than the threshold and maximally reserves the true signal using a multinomial. Compared with the soft and hard threshold function, the new threshold function shows perfect performance with different SNR. Simulation shows that, compared with traditional fixed threshold wave filtering, the new method can effectively eliminate noise, and improve FOG＇s bias stability, random walking and other technique parameters.