The theory of wavelet transform is used in the processing of the MEMS Gyro signals,and according to two states of the MEMS Gyro, filtering results using the Daubechies(Db) wavelets are analyzed,comparing to the filtering result using a two order IIRfilter.

According to the algorithms of wavelet theory and soft-threshold filtering,the MATLAB simulation on four kinds of typical signal and gyro signal was studied.

MEMS gyroscope’s error modeling based on wavelet neural network of genetic algorithms;

Research of De-noise algorithms in MEMS gyroscope based on DSP;

Data analysis and modeling research of MEMS gyroscope drift;

Research on filter method and model of MEMS gyro static drift;

Application of the adaptive kalman filter in the MEMS gyro signal processing;

Based on the analysis of the existing soft threshold and hard threshold wavelet denoising methods,an improved wavelet threshold denoising method is presented which integrated the advantages of the above two methods,and was applied into the filtering process of the MEMS gyro’s signal.

Inertia measure using MEMS gyroscope;

Device level vacuum packaging technologies of MEMS gyroscopes

The compensating method for MEMS gyroscope random drift error is discussed.

Duffing-oscillator-based detection of periodic weak signals of MEMS gyro;

Wavelet threshold de-noising for MEMS gyro

A low cost scheme of the full attitude detection system composed of magnetometers and MEMS gyroscope was proposed.