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为补偿漂移误差对硅微陀螺的测量精度造成的损失,针对漂移误差易受外部环境噪声影响的特点,提出了一种基于前向线性预测(FLP)的小波变换(WT)处理方法——DWT-FLP 算法,并通过硅微陀螺试验对其进行了验证。该方法利用快速小波变换算法进行信号的小波分解和小波重构,并将 FLP 方法用于小波分解系数的重构,比较显著地提高了重构信号的精度。对于4尺度的 db4小波变换,40阶 FLP 的滤波方法可以将硅微陀螺静态漂移的标准差提高4.8倍,动态测量过程信噪比可以提高6.5dB,并且该算法的实时性也可以满足实际工程的需要。
In order to compensate for the loss caused by drifting errors on the measurement accuracy of silicon micro-gyroscopes, a novel wavelet transform (WT) method based on Forward Linear Prediction (FLP) is proposed to deal with the problem that drift error is easily affected by external environment noise. DWT -FLP algorithm, which is verified by silicon micro-gyro test. The method uses fast wavelet transform algorithm for wavelet decomposition and wavelet reconstruction, and uses FLP method to reconstruct the wavelet decomposition coefficient, and remarkably improves the accuracy of the reconstructed signal. For the 4-scale db4 wavelet transform, the 40-order FLP filtering method can increase the standard deviation of the MEMS microdroplet static drift by 4.8 times, and the signal-to-noise ratio of the dynamic measurement process can be increased by 6.5dB, and the real-time performance of the algorithm can also satisfy the actual project Need.