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地基雷达干涉仪IBIS系统,因其监测精度高,全天候易安装等优点,目前已经广泛应用于大型工程的精密监测中。但是,由于监测中会有各种噪声源的存在,使测量数据中混入噪声进而影响到监测精度。本文利用奇异值分解(Singular Value Decomposition)对监测的时序数据进行多维分解,保留主要的形变成分并去除噪声成分,最后重建得到较高精度的实时监测结果。
Ground-based radar interferometer IBIS system, because of its high monitoring accuracy, easy to install around the clock, etc., has been widely used in large-scale project of precision monitoring. However, due to the existence of various noise sources during the monitoring, the measurement data is mixed with noise and the monitoring accuracy is affected. In this paper, the singular value decomposition (Singular Value Decomposition) is used to decompose the monitored time-series data in multi-dimensions. The main deformation components are preserved and the noise components are removed. Finally, the real-time monitoring results with higher accuracy are reconstructed.