基于提升小波的MEMS陀螺去噪方法研究

微机电系统(MEMS)陀螺的随机漂移误差是传感器的主要误差,传统硬、软阈值去噪法在去噪效果和实时性方面存在不足。该文从提升小波变换的基本理论出发,分析了提升小波阈值去噪原理,提出了基于提升小波的改进阈值去噪算法,并结合MEMS陀螺输出数据,并对硬、软阈值去噪法与改进阈值去噪法的仿真实验进行比较分析。仿真结果表明,改进阈值去噪法获得了更高的信噪比83.532 7dB,其去噪效果明显优于硬、软阈值,且运算速度较快,更适合实际运用。

Study on De noising Method in MEMS Gyroscope Based Lifting Wavelet

The random shift error of MEMS gyroscope is the main error of this kind of sensor and the conventional de-noising method with the hard and soft threshold has some shortages in the de-noising effect and the real-time ability.In this work,the de-noising principle of the lifting wavelet threshold has been analyzed based on the basic theory of the lifting wavelet transform and an improved threshold de-noising method based on the lifting wavelet has been proposed.Combining with MEMS gyroscope output data,the simulation experiments of the de-noising method with hard and soft threshold and the improved threshold de-noising method have been compared and analyzed.The results showed that the higher signal-noise ratio of 83.5327 dB has been obtained by using the improved threshold de-noising method.Moreover,the method proposed in this work has better de-noising effect and faster process speed comparing with the conventional de-noising method with the hard and soft threshold,thus is more suitable for the applications.