基于SVD/小波的MEMS陀螺误差分析及降噪处理

Error analysis and noise reduction of MEMS gyro based on SVD/wavelet

陀螺仪作为导航系统的核心传感器,其输出信号的精度对导航结果有着重要的影响。针对微机电系统(micro electro mechanical system,MEMS)陀螺成本低、应用广泛但精度低、噪声大的使用现状,选取小波分析方法对MEMS陀螺信号进行误差分析,针对误差分析结果提出了一种小波分析结合奇异值分解(singular value decomposition,SVD)的降噪方法以剔除微弱噪声信号。针对小波分析存在的小波分解层数和小波系数难以选取的问题,提出一种自适应选取小波分解层数和变换小波系数的改进小波算法;通过引入SVD以改进小波变换检测微弱信号中噪声的劣势问题,设计双轴电动转台的静、动态试验,静态试验进行信号的误差分析,动态试验验证改进算法的精度,得出改进算法比之传统小波算法降噪性能提升的结论。

Gyroscope is the core sensor of the navigation system,and the accuracy of its output signal has an important impact on the navigation results.Micro-mechanical(MEMS)gyro is a low-cost sensor with wide application,low precision and high noise.For its current use,wavelet analysis method is used to analyze the error of MEMS gyro signal.A method of noise reduction based on wavelet analysis combined with singular value decomposition(SVD)to eliminate weak noise signals is proposed.Firstly,an improved wavelet algorithm for adaptively selecting wavelet decomposition layer and transforming wavelet coefficients is proposed for the problem that the wavelet decomposition layer and wavelet coefficients are difficult to select.Secondly,SVD is introduced to improve the disadvantage of wavelet transform algorithm for detecting noise in weak signals.Finally,the static and dynamic tests of the two-axis electric turret are designed.The static test carries out the error analysis of the signal,and the dynamic test verifies the accuracy of the improved algorithm,and it is concluded that the improved algorithm has improved noise reduction performance compared with the traditional wavelet algorithm.