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The Application of Improved Data Processing Methods in GNSS Displacement Monitoring Systems

IPICE '24 Proceedings of the 2024 International Conference on Image Processing, Intelligent Control and Computer Engineering(2024)

Qingdao University of Technology

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Abstract
Since the GNSS displacement monitoring system is often arranged in the field and affected by hardware equipment, environmental changes, and communication links, there are often outliers in the GNSS displacement data obtained, making it difficult to reflect the real displacement characteristics. To address this problem, this paper proposes an improved data processing method: for a set of displacement observation data, construct the indirect leveling formula of displacement residuals, use the IGG III model combined with cubic spline interpolation to detect the outliers in the displacement data, reject the detected outliers, and fill in the data gaps arising from the outlier rejection to maintain the temporal continuity of the data and improve data quality. Through this method, not only are the outliers effectively eliminated, but the continuity and quality of the data are also guaranteed by the interpolation technique. This paper demonstrates that this method can reasonably and accurately eliminate the outliers and effectively fill in the missing displacement data after the elimination of these outliers when abnormal changes occur in GNSS displacement monitoring data, providing high-quality displacement data for subsequent analysis and prediction.
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