超声波测距系统中的小波去噪方法研究

针对远距离超声波测距系统中回波信号信噪比低的问题,采用小波变换对超声波的回波信号进行去噪处理。为取得较好的去噪效果,对小波变换的参数选取进行了研究。根据小波基的特性,通过能量与能量熵选取最优小波基;基于回波信号噪声的白噪声特征,采用白噪声检验自适应确定分解层数;引入参考噪声信号,确定小波系数处理阈值,并选用一种结合软、硬阈值函数的改进阈值函数进行小波系数处理。为验证方法的有效性,搭建基于NI数据采集卡和LabVIEW的超声回波信号采集平台,利用MATLAB小波工具包完成回波信号的去噪处理,并通过信噪比、均方根误差等指标对去噪效果进行综合评判。实验表明小波去噪可以达到很好的去噪效果,为大量程超声测距提供理论基础。

Research on Wavelet Denoising Method in Ultrasonic Ranging System

Aiming at the problem of low signal-to-noise ratio of echo signal in long-distance ultrasonic ranging system,wavelet transform was used to denoise the echo signal of ultrasonic.In order to get better denoising effect,the selection of wavelet transform parameters were studied.According to the characteristics of the wavelet base,the optimal wavelet base was selected by energy and energy entropy.Based on the white noise characteristics of the echo signal noise,the white noise test was used to determine the number of decomposition layers adaptively.The reference noise signal was introduced to determine the wavelet coefficient processing threshold,and an improved threshold function combining soft and hard threshold functions were selected for wavelet coefficient processing.In order to verify the validity of the method,an ultrasonic echo signal acquisition platform based on NI data acquisition card and LabVIEWwas set up.The MATLAB wavelet toolkit was used to complete the denoising process of the echo signal,and the denoising effect was comprehensively evaluated by signal-to-noise ratio and root-mean-square error.Experiments shows that wavelet denoising can achieve a good denoising effect and provide a theoretical basis for large-range ultrasonic ranging.