边坡安全监测GPS-RTK信号的降噪算法研究

Denoising algorithm for GPS-RTK signals in slope safety monitoring

全球定位系统实时动态差分技术(global positioning system-real time kinematic, GPS-RTK)是解决路基边坡安全监测问题的重要手段,但GPS-RTK信号易受到多路径误差和共模误差的影响。基于小波变换(wavelet transform, WT)和主成分分析(principal component analysis, PCA)分别可以有效去除多路径误差和共模误差,提出WT-PCA算法去除信号误差。首先设置仿真信号,通过参数调优进一步提高单一算法的降噪效果。其次提出组合算法WT-PCA改进单一算法的缺陷,并与其他组合算法进行对比分析。最后,对十天高速路基边坡的GPS-RTK监测数据进行实例分析。结果表明,WT-PCA算法的信噪比和均方根误差较于WT-VMD优于66%和50%左右,算法可以有效地消除GPS-RTK信号的多路径误差和共模误差影响。提高边坡位移监测信号处理精度,进一步评估边坡结构形变及安全状态。

Global positioning system-real time kinematic(GPS-RTK)is an important means to solve the safety monitoring problem of roadbed slopes,but GPS-RTK signals are susceptible to multipath errors and common mode errors.Here,based on wavelet transform(WT)and principal component analysis(PCA)being able to effectively remove multipath errors and common mode errors,WT-PCA algorithm was proposed to remove signal errors.Firstly,simulation signals were set up,and the denoising effect of a single-algorithm was further improved through parametric tuning.Secondly,the proposed combination algorithm WT-PCA was used to improve shortcomings of a single-algorithm and contrastive analysis was performed between WT-PCA combination algorithm and other combination algorithms.Finally,an actual example analysis was performed for GPS-RTK monitoring data of 10-day high-speed roadbed slope.The results showed that signal-to-noise ratio(SNR)and RMS error of WT-PCA algorithm are better than those of WT-VMD by about 66%and 50%,respectively;WT-PCA algorithm can effectively eliminate effects of multipath errors and common mode errors of GPS-RTK signals,and improve the accuracy of slope displacement monitoring signal processing for further evaluating deformation and safety status of slope structure.