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中文摘要：
大气效应尤其是大气水汽含量在时间和空间上变化引起的雷达信号传播延迟,是重轨雷达干涉测量中难以消除的主要误差源之一。当缺乏外部水汽改正数据且仅有少量SAR数据无法进行时间序列方法大气分离情况的大气改正,可利用大气延迟相位与地形的回归性分析进行一定的大气延迟改正。本文针对回归性分析中特征点的选取提出了区间中位数选样方法,并利用Akaike信息准则对大气延迟相位与地形回归模型进行了评价。实验研究表明了本文提出方法的有效性,为InSAR中大气延迟改正提供了参考。
英文摘要：
Atmospheric effects, especially the radar signal propagation delay caused by spatiotemporal changes in atmospheric water vapor content, are one of the main error sources in repeat-pass interferometry SAP. When there is no external water vapor data and too few SAP, images to conduct the atmospheric delay correction, it is possible to use a regression analysis between the atmospheric delay phase and the topography to obtain the atmospheric delay correction. Regarding the problem of selecting feature points, in this paper we provide a Section Median Method （SMM） to improve model precision, and the regression model is evaluated using the Akaike information criterion. The experimental results show that the method proposed in this paper is effective and can provide a means capable of InSAR atmospheric delay phase correction.
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