重构小波阈值的微机电系统-惯性测量单元降噪处理

Denoising Processing of Micro Electro Mechanical System-inertial Measurement Unit Based on Reconstructed Wavelet Threshold

针对随机误差对微机电系统-惯性测量单元(micro electro mechanical systems-inertial measurement unit,MEMS-IMU)输出数据精度的影响,利用离散小波变换可降噪的特点,对MEMS-IMU数据进行降噪处理。在小波降噪过程中,阈值的估计以及阈值函数的选取直接关系到降噪的质量,构建一个新的阈值函数,通过调节阈值函数中的比例因子,解决传统多重小波分解重构在降噪方面的不足。实测数据的处理结果表明:在小波降噪过程中,新的阈值函数能够有效抑制MEMS-IMU中随机误差的影响,与传统小波降噪相比,新的阈值函数降噪后,信号具有更佳的平滑度,能够有效提高捷联惯性导航系统的定位定姿精度。

In order to know how random errors influence the output data accuracy of micro electro mechanical systems-inertial measurement unit(MEMS-IMU),the discrete wavelet transform was applied to reduce the noise of micro electro mechanical systems-inertial measurement unit(MEMS-IMU)data.In the process of wavelet denoising,the estimation of threshold and the selection of threshold function are directly related to the quality of denoising.A new threshold function was constructed and the problem of traditional multiple wavelet decomposition and reconstruction got solved by adjusting the scale factor in the threshold function.The processing results of the measured data show that the new threshold function can effectively suppress the influence of random errors in the MEMS-IMU during the wavelet denoising process.Compared with the traditional wavelet denoising,the new threshold function has better signals after noise reduction,which can effectively improve the positioning and attitude accuracy of strap down inertial navigation system.