New digital drive phase control for improving bias stability of silicon MEMS gyroscope

In order to improve the bias stability of the micro-electro mechanical system（MEMS） gyroscope and reduce the impact on the bias from environmental temperature,a digital signal processing method is described for improving the accuracy of the drive phase in the gyroscope drive mode.Through the principle of bias signal generation,it can be concluded that the deviation of the drive phase is the main factor affecting the bias stability.To fulfill the purpose of precise drive phase control,a digital signal processing circuit based on the field-programmable gate array（FPGA） with the phase-lock closed-loop control method is described and a demodulation method for phase error suppression is given.Compared with the analog circuit,the bias drift is largely reduced in the new digital circuit and the bias stability is improved from 60 to 19 °/h.The new digital control method can greatly increase the drive phase accuracy,and thus improve the bias stability.

Noise estimation and filtering method of MEMS gyroscope based on EMMAP

Aiming at the problems of low measurement accuracy,uncertainty and nonlinearity of random noise of the micro electro mechanical system(MEMS)gyroscope,a gyroscope noise estimation and filtering method is proposed,which combines expectation maximum(EM)with maximum a posterior(MAP)to form an adpative unscented Kalman filter(UKF),called EMMAP-UKF.According to the MAP estimation principle,a suboptimal unbiased MAP noise statistical estimation model is constructed.Then,EM algorithm is introduced to transform the noise estimation problem into the mathematical expectation maximization problem,which can dynamically adjust the variance of the observed noise.Finally,the estimation and filtering of gyroscope random drift error can be realized.The performance of the gyro noise filtering method is evaluated by Allan variance,and the effectiveness of the method is verified by hardware-in-the-loop simulation.

An improved noise reduction transformation for algorithm based on wavelet MEMS gyroscope

To solve the large noise problem for the low- precision gyroscopes in micro-electro mechanical systems （MEMS） of inertial navigation system, an improved noise reduction method, based on the analyses of the fast Fourier transformation （FFT） noise reduction principle and the simple wavelet noise reduction principle, was proposed. Furthermore, the FFT noise reduction method, the simple wavelet noise reduction method and the improved noise reduction method were comparatively analyzed and experimentally verified in the case of the constant rate and dynamic rate. The experimental analysis results showed that the improved noise reduction method had a very good result in the noise reduction of the gyroscope data at different fi：equencies, and its performance was superior to those of the FFT noise reduction method and the simple wavelet noise reduction method.