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Time-series InSAR tropospheric atmospheric delay correction based on common scene stacking

  • role： First author第一作者
  • Affiliation：

    School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

  • Email：lisihui@whu.edu.cn
  • Introduction：李思慧，研究方向为InSAR地表形变监测。E-mail：lisihui@whu.edu.cn
LI Sihui1,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

  • Email：dongjie@whu.edu.cn
  • Introduction：董杰，研究方向为时间序列InSAR算法及其在地表形变监测中的应用。E-mail：dongjie@whu.edu.cn
DONG Jie1*,  
  • Affiliation：

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

ZHANG Lu2,  
  • Affiliation：

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

LIAO Mingsheng2

resumen

Synthetic Aperture Radar Interferometry (InSAR) technology has the advantages of high resolution, high precision, and wide coverage; it has been widely used in the field of ground deformation monitoring. However, the tropospheric atmospheric delay has always been one of the main factors limiting the accuracy of deformation measurement of InSAR. Given that the interferograms sharing a common scene contain the same contribution of atmospheric delay, the Common Scene Stacking (CSS) method uses simple summation to estimate the atmospheric delay phase of the common date and improves the estimation accuracy through iterations with the advantages of simple implementation and high computational efficiency. The CSS method estimates the atmospheric delay phase point by point, thereby introducing more noise. The estimated atmospheric delay phase by CSS is spatially low-pass filtered in this study given the characteristics of the atmospheric delay phase as a low-frequency component in the spatial dimension, and the phase unwrapping and CSS atmospheric delay phase estimation are iterated to improve the deformation estimation results. The influence of different parameters on the tropospheric atmospheric delay correction results of CSS is analyzed using simulated data. The results show that satisfactory results can be obtained after five iterations. Then, this method is applied to real SAR data. The comparison of the results of different time windows indicates that using a larger time window smoothens the time series of stable points. However, at the same time, it leads to distortion at both ends of the time series of deformation points. The proposed method is compared with spatio-temporal filtering, GACOS, and IPTA methods, and the correction result of the CSS method is found to be significantly better than that of spatio-temporal filtering and GACOS. After correction by the CSS method, the spatial phase standard deviation is reduced by 62% on the average, and the time-series standard deviation of the stable points is reduced by 58% on the average. Compared with IPTA, the CSS method can obtain similar results and improve the problem of underestimation of deformation. On this basis, the applicability of the CSS method for the vertically stratified tropospheric delay is discussed. The simulation results show that the CSS method can only correct the turbulent mixing delay, but cannot effectively remove the vertically stratified delay. Therefore, the CSS method is unsuitable for the steep mountainous areas, where the vertically stratified component is evident and the atmospheric delay presents a seasonal oscillation trend.

palabra clave

time-series InSAR;tropospheric atmospheric delay;common scene stacking;parameters setting;deformation estimation

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