基于S-变换的GNSS滑坡变形监测数据信息提取与抑噪

提出一种基于S-变换的变形监测数据抑噪方法。首先采用S-变换对监测数据进行时频分析，得到二维时频矩阵，再根据二维时频矩阵设计时频滤波器，最后利用时频分析反变换方法重构信号。采用模拟数据和滑坡变形实测数据对该方法的有效性进行验证。结果表明，相较于小波滤波方法，经该方法处理后的变形数据的RMSE和SNR均较优，可准确提取监测点的变形特征，为滑坡变形预测预报提供可靠的监测数据。

Information Extraction and Noise Suppression of GNSS Landslide Deformation Based on S-Transformation

We propose a denoising method based on S-transformation for deformation monitoring data. Firstly, we perform time-frequency analysis of the monitoring data by S-transformation, and obtain the two-dimensional time-frequency matrix. Then, we design the time-frequency filter according to the two-dimensional time-frequency matrix. Finally, we use the time-frequency analysis inverse transform method to reconstruct the signal. The effectiveness of the method is verified by simulation data and landslide deformation data. The results show that compared with the wavelet filtering method, the deformation data processed by the S-transformation filtering method is superior in both RMSE and SNR, which can accurately extract the deformation characteristics of the monitoring points.