Random Noise Compensation Method for MEMS Accelerometer Based on EMD Decomposition
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摘要: 为提高MEMS加速度计测量精度,采用了一种基于经验模态分解法(EMD)的随机误差补偿方法。文中通过EMD算 法将加速度计信号分解为本征模态函数(IMFs)和一个残余分量,将IMF分为噪声主导分量、信号/噪声混合分量及信号主导分 量三类:通过阈值处理实现信号/噪声混合分量降噪;将经过降噪的信号/噪声混合分量与信号主导分量进行重构,得到降噪后 的加速度计信号。通过仿真动态数据验证和静态采集数据验证,证明算法有效提高了加速计的测量精度。Abstract: In order to improve the measurement accuracy of MEMS accelerometers, a stochastic error compensation method based on empirical mode decomposition (EMD) is adopted. In this paper the accelerometer signal is decomposed into intrinsic mode function (IMFs) and a residual component by EMD algorithm, and IMF is divided into three categories: noise dominant component, signal/noise mixed component and signal dominant component; noise reduction of signal/noise mixed component is realized by threshold processing, the signal/noise mixed component after noise reduction and the dominant component of the signal are reconstructed to obtain the accelerometer signal after noise reduction. It is proved that the algorithm can effectively improve the measuring accuracy of the accelerometer through the verification of dynamic data and static data acquisition.
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