首页> 外文会议>International conference on integration and commercialization of micro and nano systems (MNC2007 - MicroNanoChina07) >A NOVEL DEMODULATION SCHEME IN THE DIGITAL READOUT SYSTEM FORA MICRO-MACHINED GYROSCOPE
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A NOVEL DEMODULATION SCHEME IN THE DIGITAL READOUT SYSTEM FORA MICRO-MACHINED GYROSCOPE

机译:微机械陀螺仪数字读出系统中的新型解调方案

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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 0.005[deg/ ] 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.
机译:针对微机械陀螺仪的数字读出系统,提出了一种基于Sage-Husa自适应卡尔曼滤波算法的新型解调方案。在对陀螺仪检测信号进行分析的基础上,建立了加性高斯白噪声条件下的检测信号数学模型,并给出了解调方案的状态和观测模型。此外,该仿真系统由Matlab / Simulink构建。假设角速度的输入信号是阶跃正弦函数,并且检测信号中噪声的统计特性未知,则进行仿真以解调具有不同SNR(信噪比)的检测信号。另外,对模拟读出系统中的相敏解调方案进行了仿真以进行比较。结果表明,当角速度输入为0.005°s时,解调增益分别达到+ 24.23dB(输入SNR高于-12.04dB)和+ 23.92dB(输入SNR高于-16.99dB)。阶跃函数,而正弦函数为0.005 sin(2 50)°tsπΩ=×。同时,解调增益随着检测信号的SNR降低而增加。与模拟相敏解调方案相比,采用Sage-Husa自适应卡尔曼算法的解调输出收敛时间更短,但MSE(均方误差)高约5dB。综上所述,采用Sage-Husa自适应Kalman滤波算法的新型解调方案可以实时,准确地估计陀螺仪检测信号中动态噪声的协方差,并大大提高解调信号的SNR。它可以准确,快速地解调角速度,并具有良好的实用性。

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