【摘要】 为了克服InSAR技术获取数据时,由于部分月份缺失影像,而导致对研究区进行长时间序列形变分析时,所获取的形变序列为非等时距,不利于系统地反映其形变趋势的问题。本文基于MATLAB软件进行插值算法编写,对缺失时间跨度同的两种地表形变监测数据,分别进行多种插值算法实验。实验结果显示:对于缺失月份较少的数据,三次样条插值拟合效果最好;对缺失较多月份或分布不均匀的数据,立方插值拟合效果最好;线性插值和邻近点插值的拟合效果较差,不适用于对缺失的数据进行插值。该结果对由于缺失部分数据而影响其形变时序分析的情况提供了方法指导,具有较强的实用意义。更多还原

【Abstract】 In order to overcome the InSAR technology acquisition data, due to the lack of images in some months,the long-term sequence deformation analysis of the study area, the obtained deformation sequence was non-equal time interval, which is not conducive to systematically reflect the deformation trend. In this paper, based on MATLAB software, the interpolation algorithm was written. For the two kinds of surface deformation monitoring data with the same time span, a variety of interpolation algorithm experiments were carried out. The experimental results showed that for the missing data, the cubic spline interpolation has the best effect. For the data with more months or uneven distribution, the cubic interpolation fits best; linear interpolation and adjacent point interpolation Poor effect, not suitable for interpolating missing data. This result provides a methodological guidance for the situation that affects the deformation timing analysis due to the missing part of the data,and has a strong practical significance.更多还原