基于提升小波变换的矿区地表形变监测数据处理研究

Research on Data Processing of Surface Deformation Monitoring in Mining Area Based on Lifting Wavelet Transform

利用全球导航卫星系统(Global Navigation Satellite System,GNSS)对矿区地表形变进行监测时,获取的形变信号常含有较多的无效信息,严重影响了有效形变信息的提取.为了解决该问题,在现有研究成果的基础上,以河南某矿区的GNSS监测数据为研究对象,将提升小波变换方法引入到GNSS监测数据处理中,对多个监测点的监测数据进行了提升小波降噪及分解解算处理,并通过对比试验验证了提升小波降噪解算方法的有效性.结果表明,矿区复杂环境下的GNSS监测数据中包含大量的噪声信息,若直接进行解算容易导致获取的形变量失真,而利用提升小波变换对GNSS监测数据进行降噪处理之后再进行解算,有助于减少干扰噪声的影响、分离出有效形变信息、提高GNSS监测数据的解算精度和稳定性.本研究可为GNSS监测数据的处理及矿区地表形变监测提供参考.

When global navigation satellite system(GNSS)is used to monitor surface deformation in mining area,the obtained deformation signals often contain a lot of invalid information,which seriously affects the extraction of effective deformation information. In order to solve the problem,on the basis of existing research results,taking the GNSS monitoring data of a mining area in Henan Province as the research object,the lifting wavelet transform method is introduced into GNSS monitoring data processing. The monitoring data of multiple monitoring points are processed by lifting wavelet noise reduction and decomposition algorithm,and the validity of the calculating method of the lifting wavelet noise reduction is verified by comparative tests. The results show that the GNSS monitoring data of the mining area in the complex environment contain a large amount of noise information. If the calculation is carried out directly,it will easily lead to the distortion of the obtained deformation variables. When the lifting wavelet transform is used to denoise the GNSS monitoring data before the calculation,the influence of interference noise can be reduced and the deformation information can be effectively separated,which can improve the calculation accuracy and stability of GNSS monitoring data. This study can provide reference for GNSS monitoring data processing and surface deformation monitoring in mining area.