The application of the phase reconstruction on small InSAR datasets

Kui ZHANG; Hui WANG; Ruiqing SONG; Yaobin SHENG

doi:10.11834/jrs.20175337

Views : 0 下载量: 608 CSCD: 8

PDF
Export
Share
Collection
Album

The application of the phase reconstruction on small InSAR datasets
Vol. 21, Issue 4, Pages: 645-652(2017)
Received：25 July 2016，

Accepted：16 March 2017，

Published：2017-07
DOI： 10.11834/jrs.20175337
稿件说明：

移动端阅览

张奎, 汪慧, 宋瑞庆, 盛耀彬. 2017. 相位萃取技术在InSAR小数据集上的应用. 遥感学报, 21(4): 645–652 DOI： 10.11834/jrs.20175337.

Zhang K, Wang H, Song R Q and Sheng Y B. 2017. The application of the phase reconstruction on small InSAR datasets. Journal of Remote Sensing, 21(4): 645–652 DOI： 10.11834/jrs.20175337.

摘要

相位萃取技术可最小化多基线InSAR处理中干涉像对的去相关噪声，已成为雷达干涉测量研究领域中热点技术之一。本文首先设计并实现了一套专门针对小数据集的基于相位萃取技术的多基线InSAR处理流程。整个流程分为两大模块。第一个模块为称为预处理模块，通过图像配准、地形相位移除等操作生成相位萃取技术所需的零基线SAR图像堆栈。第二个模块首先基于多视像元生成相干矩阵，并且在此基础上完成相位萃取操作。然后，利用小基线集技术的思想在萃取相位上分离出各相位稳定点上的形变情况。为了保证结果可靠性，在这一模块中还加入了大气相位预估与移除的步骤。最后，该流程被应用到了5景拍摄于太原地区的PALSAR图像上。实验结果表明，相位萃取技术在小数据集情况下仍然能够有效提升数据的相干性，这有利于多基线InSAR输出结果密度的提升。

Abstract

Multi-baseline InSAR techniques have demonstrated their great potential in topographic mapping and ground surface deformation monitoring. In order to minimize the decorrelation noise between stacked SAR images in multi-baseline InSAR processes

the phase reconstruction technique has been developed recently and has become one of the hotspot techniques in radar interferometry. Due to budget limitations and unstable SAR image acquisition frequency

a lot of multi-baseline InSAR applications have to be carried out based on small image datasets. Researchers have made every endeavor to address this problem

some targeted multi-baseline InSAR processing strategies have been therefore developed. Unfortunately

there are few literatures discussing the application of phase reconstruction to small image datasets at this stage. This paper aims to evaluate the effectiveness of the phase reconstruction technique on a small SAR image datasets. A targeted multi-baseline InSAR processing scheme was designed and applied to real data. The main idea of phase reconstruction technique is to reform phase observations along a SAR stack by taking advantage of a maximum likelihood estimator which is defined on the coherence matrix estimated from each target. The proposed multi-baseline InSAR processing scheme is divided into two modules. The first one is named as " pre-processing module”

which generates the zero-baseline SAR image stack required by the phase reconstruction technique via a series of operations including image coregistration

topographic phase component removal

and so on. The second one firstly constructs coherence matrices based on multilooked pixels

thereby conducting phase reconstruction operations. Subsequently

it isolates ground surface deformation signals based on reconstructed phase observations by taking advantage of the small baseline subset technique. Noted that an atmospheric disturbances estimation and removal step was involved in this module in order to assure the reliability of the output measurements. The proposed scheme is subsequently applied to five PALSAR images acquired over Taiyuan

ShanXi Province

China. During the experimental process

the performance of the phase reconstruction technique in the case of small image subsets was analyzed in different aspects (e.g. the signal-to-noise ratio of the FFT based orbital fringe estimation process

the number of residues contained in phase unwrapping networks). The corresponding annual deformation rate field was presented

as well as the distribution of additional points obtained after the application of the phase reconstruction technique. The results has demonstrated that the phase reconstruction technique can effectively improve interferometric coherence even in the case of small image datasets

which is beneficial to the proliferation of the density of multi-baseline InSAR results. It must be noted that the size of the coherence matrix is relatively small in the case of small image datasets. Thus the precision of the phase reconstruction results is likely to be influenced by the low coherent elements of coherence matrix. In order to make the phase reconstruction technique work with small image datasets better

future works should try to eliminate the negative impacts of low-quality elements on the phase reconstruction procedure.

关键词

Keywords

references

Berardino P, Fornaro G, Lanari R and Sansosti E. 2002. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing, 40(11): 2375–2383

Cao N, Lee H and Jung H C. 2015. Mathematical framework for phase-triangulation algorithms in distributed-scatterer interferometry. IEEE Geoscience and Remote Sensing Letters, 12(9): 1838–1842

Ferretti A, Fumagalli A, Novali F, Prati C, Rocca F and Rucci A. 2011. A new algorithm for processing interferometric data-stacks: SqueeSAR. IEEE Transactions on Geoscience and Remote Sensing, 49(9): 3460–3470

Ferretti A, Prati C and Rocca F. 2000. Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 38(5): 2202–2212

Ferretti A, Prati C and Rocca F. 2001. Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 39(1): 8–20

葛大庆, 郭小方, 王毅, 王艳, 刘圣伟. 2007. 基于序列差分干涉纹图的地表形变速率提取. 国土资源遥感, 19(1): 24–26

Ge D Q, Guo X F, Wang Y, Wang Y and Liu S W. 2007. Surface deformation rate derivation based on differential interferograms stack. Remote Sensing for Land and Resources, 19(1): 24–26

Guarnieri A M and Tebaldini S. 2008. On the exploitation of target statistics for SAR interferometry applications. IEEE Transactions on Geoscience and Remote Sensing, 46(11): 3436–3443

季灵运, 许建东, 赵波, 万园,申欢欢. 2013. 利用InSAR技术研究新疆阿什库勒火山群现今活动性. 地震地质, 35(3): 532–541

Ji L Y, Xu J D, Zhao B, Wan Y and Shen H H. 2013. Present-day activity of Ashikule volcanic group from InSAR. Seismology and Geology, 35(3): 532–541

Kampes B M and Hanssen R F. 2004. Ambiguity resolution for permanent scatterer interferometry. IEEE Transactions on Geoscience and Remote Sensing, 42(11): 2446–2453

李永生, 张景发, 李振洪, 罗毅. 2013. 利用短基线集干涉测量时序分析方法监测北京市地面沉降. 武汉大学学报(信息科学版), 38(11): 1374–1377

Li Y S, Zhang J F, Li Z H and Luo Y. 2013. Land subsidence in Beijing City from InSAR time series analysis with small baseline subset. Geomatics and Information Science of Wuhan University, 38(11): 1374–1377

廖明生, 唐婧, 王腾, Balz T, 张路. 2012. 高分辨率SAR数据在三峡库区滑坡监测中的应用. 中国科学:地球科学, 42(2): 217–229

Liao M S, Tang J, Wang T, Balz T and Zhang L. 2012. Landslide monitoring with high-resolution SAR data in the Three Gorges region. Science China Earth Sciences, 42(2): 217–229

Liu G X, Buckley S M, Ding X L, Chen Q and Luo X J. 2009. Estimating spatiotemporal ground deformation with improved permanent-scatterer radar interferometry. IEEE Transactions on Geoscience and Remote Sensing, 47(8): 2762–2772

刘振国, 卞正富, 吕福祥, 董保权. 2013. 时序DInSAR在重复采动地表沉陷监测中的应用. 采矿与安全工程学报, 30(3): 390–395

Liu Z G, Bian Z F, Lv F X and Dong B Q. 2013. Subsidence monitoring caused by repeated excavation with time-series DInSAR. Journal of Mining and Safety Engineering, 30(3): 390–395

Lu P, Casagli N, Catani F and Tofani V. 2012. Persistent scatterers interferometry hotspot and cluster analysis (PSI-HCA) for detection of extremely slow-moving landslides. International Journal of Remote Sensing, 33(2): 466–489

Mora O, Mallorqui J and Broquetas A. 2003. Linear and nonlinear terrain deformation maps from a reduced set of interferometric SAR Images. IEEE Transactions on Geoscience and Remote Sensing, 41(10): 2243–2253

吴宏安, 张永红, 陈晓勇, Zhong L, 都洁, 孙中惠, 孙广通. 2011. 基于小基线DInSAR技术监测太原市2003~2009年地表形变场. 地球物理学报, 54(3): 673–680

Wu H A, Zhang Y H, Chen X Y, Zhong L, Du J, Sun Z H and Sun G T. 2011. Ground deformation monitoring using small baseline DInSAR technique: a case study in Taiyuan City from 2003 to 2009. Chinese Journal of Geophysics, 54(3): 673–680

吴涛, 张红, 王超, 汤益先, 吴宏安. 2008. 多基线距DInSAR技术反演城市地表缓慢形变. 科学通报, 53(15): 1849–1857

Wu T, Zhang H, Wang C, Tang Y X and Wu H A. 2008. Retrieval of urban slow deformation using the multi-baseline DInSAR technique. Chinese Science Bulletin, 53(15): 1849–1857

许才军, 何平, 温扬茂. 2011. 利用PSInSAR研究意大利Etna火山的地表形变. 武汉大学学报(信息科学版), 36(9): 1012–1016

Xu C J, He P and Wen Y M. 2011. Surface deformation of Mt. Etna, Italy from PSInSAR.Geomatics and Information Science of Wuhan University, 36(9): 1012–1016

徐小波, 屈春燕, 单新建, 马超, 张桂芳, 孟秀军. 2012. 基于PS-InSAR技术的断裂带地壳形变实验研究. 地球科学进展, 27(4): 452–459

Xu X B, Qu C Y, Shan X J, Ma C, Zhang G F and Meng X J. 2012. An experimental study of monitoring fault crustal deformation using PS-InSAR technology. Advances in Earth Science, 27(4): 452–459

尹宏杰, 朱建军, 李志伟, 丁晓利, 汪长城. 2011. 基于SBAS的矿区形变监测研究. 测绘学报, 40(1): 52–58

Yin H J, Zhu J J, Li Z W, Ding X L and Wang C C. 2011. Ground subsidence monitoring in mining area using DInSAR SBAS algorithm. ActaGeodaeticaet CartographicaSinica, 40(1): 52–58

张景发, 龚利霞, 姜文亮. 2006. PS InSAR技术在地壳长期缓慢形变监测中的应用. 国际地震动态(6): 1–6

Zhang J F, Gong L X and Jiang W L. 2006. Application of PS InSAR technique to measurement of long-term crustal deformation. Recent Developments in World Seismology(6): 1–6

Zhang K, Ge LL, Li X J and Ng A H M. 2012. Monitoring ground surface deformation over the North China Plain using coherent ALOS PALSAR differential interferograms. Journal of Geodesy, 87(3): 253–265

Alert me when the article has been cited

提交

The role and potential of Moon-based observations of Earth’s radiation energy and solid tides

Synthetic Aperture Radar Analysis Ready Data （SAR ARD）： Progress， challenges and prospects

Research progress on Synthetic Aperture Radar in lunar exploration

Ocean internal wave detection in SAR images by combining superpixel segmentation and saliency features

Flood monitoring and analysis based on time-series SAR image for complex area