A NOVEL DEMODULATION SCHEME IN THE DIGITAL READOUT SYSTEM FORA MICRO-MACHINED GYROSCOPE
A novel demodulation scheme with Sage-Husa adaptive Kalman filtering algorithm is presented for the digital readout system of a micro-machined gyroscope. Based on the analysis of the detection signal from gyroscope, a mathematical model of the detection signalis established in the condition of the additive white Gaussian noise, and the state and observation model for the demodulation scheme are also given. Moreover, the simulation system is built by the Matlab/Simulink. Assuming the input signal of angular velocity is the stepor sine function, and the statistical characteristics of the noise in the detection signal are unknown, simulations are given to demodulate the detection signal with different SNRs (signal-to-noise ratio). In addition, the phase sensitive demodulation scheme in the analog readout system is simulated for comparison. Results show that, the demodulation gains reach +24.23dB (input SNR is above -12.04dB) and +23.92dB (input SNR is above -16.99dB) respectively when the angular velocity input is 0.005deg/ s Ω=for the step function, while 0.005 sin(2 50 )deg/ t s π Ω=× for the sine function. Meanwhile, the demodulation gain increases along with the decreasing SNR of the detection signal. Comparedwith the analog phase sensitive demodulation scheme, the demodulation output with Sage-Husa adaptive Kalman algorithm has the shorter convergence time, but about 5dB higher of MSE (mean square error). In conclusion, the novel demodulation scheme withSage-Husa adaptive Kalman filtering algorithm can real-timely and precisely estimate the covariance of dynamic noise in the detection signal from gyroscope, and increase the SNR of the demodulation signals dramatically. It can demodulate the angular velocity accurately and quickly, and shows a good practicability.
micro-machined gyroscope digital readout system demodulation Kalman filtering
Lu Liu Yi-chao Song Xu-zong Chen
School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China
国际会议
海南三亚
英文
2007-01-10（万方平台首次上网日期，不代表论文的发表时间）