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针对现有去噪方法中存在的噪声信号提取、粗差定位等问题,该文基于小波阈值去噪的原理,提出一种基于软阈值改进的模平方阈值去噪法。通过仿真数据实验对比分析了软阈值去噪法、加权平均阈值去噪法及模平方阈值去噪法的去噪实际效果,并应用于汽车试验场沉降数据预处理。实验结果表明,基于模平方的阈值去噪法能够较好地保留观测信号原始信息,并且可以有效地去除噪声,其去噪效果优于软阈值和加权平均阈值去噪法,能在汽车试验场沉降数据处理中得到较好的应用。
Aiming at the problems of noise signal extraction and gross error location existing in the existing denoising methods, this paper proposes a denoising method of squared squared threshold based on improved soft threshold based on the principle of wavelet threshold denoising. Through the simulation data experiment, the soft threshold de-noising method, the weighted average threshold de-noising method and the modular squared threshold de-noising method are compared and the de-noising method is applied to the data pre-processing of the settlement of the vehicle test ground. The experimental results show that the threshold-based denoising method based on the square-squared method can preserve the original information of the observed signal well, and can effectively remove the noise. The denoising effect is better than the soft threshold and the weighted average threshold denoising method, Settlement data processing get better application.