PCA与Welch相结合的开采沉降实时观测坐标序列分析

    Analysis of Real-time Observation Coordinate Sequence for Mining Subsidence by PCA and Welch

    • 摘要: 针对矿区开采沉降GPS变形监测坐标序列中存在的共模误差,利用PCA主成分分析方法,将高频单历元解算中的测站之间相关性误差提取并消除。利用Welch频谱法分析PCA空间滤波消除共模误差的周期频率特性。最后,处理某矿区实时GPS变形监测网中的观测沉降数据,验证了PCA空间滤波方法在去除共模误差的可行性,提高了矿区开采沉降GPS观测精度。

       

      Abstract: For the common mode error in GPS deformation monitoring coordinate sequence of mining subsidence, the principal component analysis (PCA) was used to extract and eliminate the correlative error among stations in high frequent single epoch algorithm. Welch spectrum method is used to analyze the cycle frequency characteristics of using PCA space filtering to eliminate common-mode error. Finally, we process real-time settlement observation data from GPS deformation monitoring network in a certain mining area, and verify the feasibility of removing common-mode error by PCA spatial filtering method. The method improves the precision of mining subsidence with GPS observation.

       

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