基于改进的 Sage-Husa 滤波 MEMS陀螺阵列降噪技术研究

为充分挖掘 MEMS 陀螺的性能,提高 MEMS 陀螺在实际应用中的精度,通过搭建四陀螺阵列结合改进的 Sage-Husa 滤 波算法对陀螺阵列的输出信号进行降噪,在不改变陀螺加工工艺和显著提高生产成本的条件下有效提高了 MEMS 陀螺仪的实 际性能。 通过分析 MEMS 陀螺仪的系统误差和随机误差,搭建误差模型,利用传统卡尔曼滤波、移动平均滤波、小波阈值去噪 和改进的 Sage-Husa 滤波算法对单个陀螺和陀螺仪阵列进行降噪处理,实验对比发现改进的 Sage-Husa 滤波算法和陀螺仪阵列 结合后能有效降低陀螺的输出噪声。 利用 Allan 方差分析陀螺仪阵列经过改进的 Sage-Husa 算法滤波后的随机误差,四陀螺阵 列角度随机游走从 0. 40°/ h降低到 0. 03°/ h ,零偏不稳定性从 71. 11°/ h 降低到 5. 83°/ h,有效提高了 MEMS 陀螺在实际应用 中的性能。

Research on noise reduction technology based on improved Sage-Husa filtered MEMS gyroscope arrays

In order to fully exploit the performance of the MEMS gyroscope and improve the accuracy of the MEMS gyroscope in practical applications,the output signal of the gyroscope array is denoised by constructing a four-gyroscope array combined with the improved SageHusa filtering algorithm. The actual performance of the MEMS gyroscope is effectively improved without changing the gyroscope processing technology and significantly increasing the production cost. By analyzing the systematic error and random error of MEMS gyroscope, the error model is built. The traditional Kalman filter, moving average filter, wavelet threshold denoising and the improved Sage-Husa filtering algorithm are used to denoise the single gyroscope and gyroscope array. Experimental comparison shows that the improved Sage-Husa filtering algorithm combined with the gyroscope array can effectively reduce the output noise of the gyroscope. The random error of the gyroscope array filtered by the improved Sage-Husa algorithm is analyzed by Allan variance. The angle random walk of the four gyroscope array is reduced from 0. 40°/ h to 0. 03°/ h , and the bias instability is reduced from 71. 11°/ h to 5. 83°/ h, which effectively improves the performance of MEMS gyroscope in practical applications.