CRInSAR大气校正及监测地表变形的研究
|
摘要
差分合成孔径雷达干涉测量技术(Differential Interferometry SyntheticAperture Radar,D-InSAR)在最近10来年有了很大的发展。但是,由于时间和空间的失相干和大气效应的影响,传统的差分干涉测量的应用受到很大的限制。永久反射器技术(permanent scatterer,PS)虽然能克服这些问题,但也有缺点,它需要有一定密度的稳定的反射点,对影像数目的要求也很高(大于30张)。为了克服以上问题,基于角反射器的合成孔径雷达干涉测量(Corner Reflector InSAR,CRInSAR)技术被提出来了。它在低相干地区的地表形变监测中具有很大应用潜力。
本文首先介绍了InSAR和D-InSAR的工作原理、数据处理流程和数据处理中的若干关键技术,介绍了目前国际上已有的CRInSAR算法理论,并特别介绍了由德国GFZ的夏耶博士提出的CRInSAR算法理论和处理流程。
然后,本文分析了CRInSAR中的大气影响。对大气的结构和成分进行了分析,根据InSAR中大气的延迟情况,将大气影响分为对流层延迟和电离层延迟。由于电离层对CRInSAR的影响很小,大气延迟的主要部分在对流层,因此本文系统分析了对流层对CRInSAR的影响,对比了现在主要的大气校正模型,最后给出了用Continuous GPS消除大气影响的算法和模型。
接着本文详细针对CRInSAR算法中相位解缠问题,提出了利用GPS整周模糊度解算中的LAMBDA方法进行相位整周模糊度搜索,并通过试验证明通过增加虚拟观测值,考虑研究区域的变形先验信息,LAMBDA方法能够成功的应用到CRInSAR技术的中来,并且结果比较符合实际的观测结果。然后在夏耶博士的CRInSAR算法的基础上改进提出了CRInSAR变形解算模型,在假设形变包括线性形变和周期性形变的基础上进行变形模型的解算。
最后,本文详细介绍了在香港地区的试验验证CRInSAR变形算法和大气改正的过程和结果。先用香港地区12个CGPS站的数据对8幅SAR图像做了大气改正,在此基础上分别用传统DInSAR和使用LAMBDA方法的CRInSAR计算了试验区域的变形状况。在两个试验区,DInSAR和CRInSAR得出了非常相似的结果,证明了CRInSAR变形监测算法的可靠性。
As well known,temporal and geometric decorrelation represents the most important limiting factors in synthetic aperture radar interferometry(InSAR) Due to this fact,analyses of low coherence areas(e.g.,forested and vegetated areas)with conventional InSAR methodologies cannot be performed successfully.Even the application of advanced InSAR algorithms,such as the permanent scatterer(PS)technique,may prove to be ineffective wherever the density of stable radar targets(i.e.,the PS)is extremely low.In order to overcome this limitation,the usage of artificial reflectors can be very promising.
In this paper,at first we give the basic theory and algorithm-processing flow chart of InSAR and DInSAR.Then,the deformation monitoring theories of CRInSAR were introduced,especially the algorithm of CRInSAR presented by Xia Y.of Germany GFZ.
Second,we analyzed structure and composition of the atmosphere.Based on the differences of effects,the layered structure of the atmosphere is redefined as tropospheric and ionospheric effects.Because the ionospheric effects are very small in CRInSAR and the majority of atmosphere effects are from tropospheric,we analyzed the tropospheric effects to CRInSAR and compare atmospheric correction models.At last,the method and process of using CGPS data to correct atmospheric effects are analyzed.
In the third part,we applied the Least Squares Ambiguity Decorrelation Adjustment(LAMBDA)method which has been applied in GPS ambiguities resolution to solve the problem of phase unwrapping,in order to solve the phase unwrapping problem of CR-InSAR.Real data is used to test the unwrapping method and reliable results are achieved compared with other method.Then the new CRInSAR algorithm was proposed.Based on the assumption that the deformation includes the linear and the periodic parts,we modeled the deformation and solved it.
At last,we investigate and compare the process and results achieved in three test fields in Hong Kong in order to demonstrate some algorisms in CRInSAR and to estimate the reliability and precision of the method in slop movement and ground deformation monitoring.We used the data from CGPS observations to correct the interferometric phases for the temporal atmospheric inhomogeneity first.Then we used the standard DInSAR and the Corner Reflectors technique(CR).The results of deformation of the CR point extracted from the DInSAR are similar with solutions from CRInSAR technique.The comparison of the results demonstrates that the Algorithms of CRInSAR are reliable and precise.
本文首先介绍了InSAR和D-InSAR的工作原理、数据处理流程和数据处理中的若干关键技术,介绍了目前国际上已有的CRInSAR算法理论,并特别介绍了由德国GFZ的夏耶博士提出的CRInSAR算法理论和处理流程。
然后,本文分析了CRInSAR中的大气影响。对大气的结构和成分进行了分析,根据InSAR中大气的延迟情况,将大气影响分为对流层延迟和电离层延迟。由于电离层对CRInSAR的影响很小,大气延迟的主要部分在对流层,因此本文系统分析了对流层对CRInSAR的影响,对比了现在主要的大气校正模型,最后给出了用Continuous GPS消除大气影响的算法和模型。
接着本文详细针对CRInSAR算法中相位解缠问题,提出了利用GPS整周模糊度解算中的LAMBDA方法进行相位整周模糊度搜索,并通过试验证明通过增加虚拟观测值,考虑研究区域的变形先验信息,LAMBDA方法能够成功的应用到CRInSAR技术的中来,并且结果比较符合实际的观测结果。然后在夏耶博士的CRInSAR算法的基础上改进提出了CRInSAR变形解算模型,在假设形变包括线性形变和周期性形变的基础上进行变形模型的解算。
最后,本文详细介绍了在香港地区的试验验证CRInSAR变形算法和大气改正的过程和结果。先用香港地区12个CGPS站的数据对8幅SAR图像做了大气改正,在此基础上分别用传统DInSAR和使用LAMBDA方法的CRInSAR计算了试验区域的变形状况。在两个试验区,DInSAR和CRInSAR得出了非常相似的结果,证明了CRInSAR变形监测算法的可靠性。
As well known,temporal and geometric decorrelation represents the most important limiting factors in synthetic aperture radar interferometry(InSAR) Due to this fact,analyses of low coherence areas(e.g.,forested and vegetated areas)with conventional InSAR methodologies cannot be performed successfully.Even the application of advanced InSAR algorithms,such as the permanent scatterer(PS)technique,may prove to be ineffective wherever the density of stable radar targets(i.e.,the PS)is extremely low.In order to overcome this limitation,the usage of artificial reflectors can be very promising.
In this paper,at first we give the basic theory and algorithm-processing flow chart of InSAR and DInSAR.Then,the deformation monitoring theories of CRInSAR were introduced,especially the algorithm of CRInSAR presented by Xia Y.of Germany GFZ.
Second,we analyzed structure and composition of the atmosphere.Based on the differences of effects,the layered structure of the atmosphere is redefined as tropospheric and ionospheric effects.Because the ionospheric effects are very small in CRInSAR and the majority of atmosphere effects are from tropospheric,we analyzed the tropospheric effects to CRInSAR and compare atmospheric correction models.At last,the method and process of using CGPS data to correct atmospheric effects are analyzed.
In the third part,we applied the Least Squares Ambiguity Decorrelation Adjustment(LAMBDA)method which has been applied in GPS ambiguities resolution to solve the problem of phase unwrapping,in order to solve the phase unwrapping problem of CR-InSAR.Real data is used to test the unwrapping method and reliable results are achieved compared with other method.Then the new CRInSAR algorithm was proposed.Based on the assumption that the deformation includes the linear and the periodic parts,we modeled the deformation and solved it.
At last,we investigate and compare the process and results achieved in three test fields in Hong Kong in order to demonstrate some algorisms in CRInSAR and to estimate the reliability and precision of the method in slop movement and ground deformation monitoring.We used the data from CGPS observations to correct the interferometric phases for the temporal atmospheric inhomogeneity first.Then we used the standard DInSAR and the Corner Reflectors technique(CR).The results of deformation of the CR point extracted from the DInSAR are similar with solutions from CRInSAR technique.The comparison of the results demonstrates that the Algorithms of CRInSAR are reliable and precise.
引文
[1]丁晓利,陈永奇,李志林,等,合成孔径雷达干涉技术及其在地表形变监测中的应用,紫金山天文台台刊,2000,Vol.19,No.2:158-167[J]
[2]程强.基于永久散射体雷达差分干涉探测区域地表形变的研究.西南交通大学博士学位论文,2006.[D]
[3]刘国祥,丁晓利,陈永奇等.极具潜力的空间对地观测新技术——合成孔径雷达干涉[J]地球科学进展,2000,(06).[J]
[4]刘国祥,丁晓利,李志林.等星载SAR复数图像的配准测绘学报,2001,(01).[J]
[5]刘国祥,丁晓利,陈永奇,等,使用卫星雷达差分干涉技术测量香港赤腊角机场沉降场,2001,Vol.46,No.14:1224-1228[J]
[6]廖明生,林珲.雷达干涉测量学:原理与信号处理基础。测绘出版社,2003.[M]
[7]李陶.重复轨道星载SAR差分干涉监测地表形变研究。武汉大学博士学位论文,2004。[D]
[8]毛建旭,王耀南,夏耶.合成孔径雷达干涉成像技术及其应用。系统工程与电子技术,Vol.25,No.1,2003.[J]
[9]谌华.CRInSAR大气校正模型研究及其初步应用.中国地震局地质研究所硕士学位论文,2006.[D]
[10]宋小刚,李德仁,廖明生等InSAR中大气改正方法的对比研究,测绘科学 Vol21 No.12007.[J]
[11]史世平,使用ERS-1/2干涉测量SAR数据生成DEM,测绘学报,2000,Vol.29,No.4:317-323.[J]
[12]王超,张红,刘智.星载合成孔径雷达干涉测量。北京:科学出版社,2002.[M]
[13]魏子卿,葛茂荣.GPS相对定位的数学模型.测绘出版社,1998.[M]
[14]许才军,王华,黄劲松.GPS与INSAR数据融合研究展望武汉大学学报·信息科学版 Vol.28特刊,2003.5.[J]
[15]张磊.利用Doris计算台湾集集地震位移场及断层滑移量反演.同济大学硕士学位论文,2006.[M]
[16]周春霞.星载SAR干涉测量技术及其在南极冰貌地形研究中的应用,武汉大学博士论文,2004.[D]
[17]Bert M.Kampes and Ramon F.Hanssen.(2004)Ambiguity resolution for Permanent Scatterer Interferometry,IEEE transactions on geoscience and remote Sensing 42(11),2446-2453.[J]
[18]Bevis,M.,S.Businger,T.A.Herring,C.Rocken,R.A.Anthes,and R.H.Ware,GPS meteorology:remote sensing of atmospheric water vapor using the Global Positioning System, Journal of Geophysical Research, 97(D14), 15,787-15,801, 1992. [J]
[19] ESA, http://earth.esa.int [DB/OL]
[20] Ding, X.L., Liu, G.X., Li, Z.W., Li, Z.L., and Chen, Y.Q. Ground subsidence monitoring in Hong Kong with satellite SAR interferometry, Photogrammetric Engineering and Remote Sensing, 70(10): 1151-1156,2004. [J]
[21] Ding, X.L., Li, Z.W., Zheng, D. W., Huang, C. and Zou, W.B. SAR interferogram filtering with 2D Vondrak filter, IEEE Geoscience and Remote Sensing Symposium, Seuol, Korea, Vol. 7, pp4825-4828, July, 2005 . [J]
[22] Ferretti, A., C. Prati, and F. Rocca, Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry, IEEE Transactions on Geoscience and Remote Sensing, 2000, Vol.38, No.5: 2202-2212. [J]
[23] Ferretti A., Prati C, Rocca F. Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, vol. 38, 5:2202-2212,2000 . [J]
[24] Ferretti, A., C. Prati, and F. Rocca, Permanent scatterers in SAR interferometry, IEEE Transactions on Geoscience and Remote Sensing, 2001, Vol.39, No.1: 8-20. [J]
[25] Ferretti A.,Guiliano Savio and Riccardo Barzaghi. Submillimeter Accuracy of InSAR Times Series:Experimental validation on IEEE Transactions on Geoscience and Remote Sensing, Vol, 45, NO5,2007. [J]
[26] Gens, R. and J.L. Van Genderen, SAR interferometry—Issues, techniques, applications, International Journal of Remote Sensing, 1996, Vol. 17, No. 10: 1803-1835. [J]
[27] R. Goldstein. 1995. Atmospheric limitations to repeat-track radar interferometry. Geophys. 22(18):2517-2520. [J]
[28] Hanssen, R., Atmospheric heterogeneities in ERS tandem SAR interferometry, 136 pp., Delft University Press, Delft, the Netherlands, 1998.. [J]
[29] Jos Groot and Matern Often. SAR Imaging of Corner Reflectors Larger Than the Spatial Resolution. IEEE Transactions on Geoscience and Remote Sensing, Vol, 32, NO. 3,1994. [J]
[30] JPL, SRTM home page, http://www.jpl.nasa.gov/srtm/ [DB/OL]
[31] Johan Jacob Mohr and Soren Norvang Madsen. Geometric Calibration of ERS Satellite SAR Images. Ieee Transactions on Geoscience and Remote Sensing, Vol, 39, No. 4, April 2001. [J]
[32] Kampes, B.M. and Usai, S., Doris: the Delft Object-oriented Radar Interferometric Software, 2nd International Symposium on Operationalization of Remote Sensing, Enschede, The Netherlands, 1999. [J]
[33] Kampes, B., Delft Object-oriented Radar Interferometric Software User's manual and technical documentation, http://www.geo.tudelft.nl/doris/, Delft University of Technology . [J] [34] Kampes, B.M (2005=). Displacement Parameter Estimation using Permanent Scatterer Interferometry.PhD thesis. Delft University of technology. [J]
[35] Li, Z.W., Ding, X.L. and Liu, G.X. (2004) Modeling Atmospheric Effects on InSAR with Meteorological and Continuous GPS Observations: Algorithms and Some Test results, Journal of Atmospheric and Solar-Terrestrial Physics, 66: 907-917. [J]
[36] Li, Z.W., Modeling Atmospheric Effect on Repeat-pass InSAR Measurements. The thesis presented for the Degree of Doctor of Philosophy, 2004. [J]
[37] Li, Z.W., Ding, X.L., Chen, Y.Q., Chen W. Assessment of Atmospheric Effects on Repeat-pass InSAR measurements in southern China region, Journal of Geospatial Engineering, 7(1): 1-10,2005. [J]
[38] Li, Z.W., X.L.Ding, C.Huang, GWadge, D.W.Zheng. Modeling of atmospheric effects on InSAR measurements by incorporating terrain elevation information. Journal of Atmospheric and Solar-Terrestrial Physics, 2006. [J]
[39] Li, Z.W., Ding, X.L., Huang, C. and Zheng, D.W. Filtering Method for Radar Interferogram with Strong noise, International Journal of Remote Sensing, 27(14): 2991-3000, 2006. [J]
[40] Liu, G.X., Ding, X.L. et al, Pre- and co-seismic ground deformations of the 1999 Chi-Chi, Taiwan earthquake, measured with SAR interferometry, Computers and Geosciences 2004, 30: 333-343. [J]
[41] Li, Z. (2005). Correction of water vapor effects on repeat-pass InSAR using GPS MODIS and MERIS data. Department of Geomatic Engineering. London, University of London. Doctor of Philosophy. [J]
[42] L. M. Ulander. Accuracy of Using Point Targets for SAR Calibration. LAE, 27:139-148, 1991. [J]
[43] Mark Haynes. Corner reflector aspects of the SNAP program: Demonstrating the utility of differential SAR interferometry for the assessment of earthquake risk. NPA Group, Crockham Park, Edenbridge, Kent TN8 6SR, U.K.2001. [J]
[44] Massonnet, D., and T. Rabaute, Radar interferometry: limits and potential, IEEE Transactions on Geoscience and Remote Sensing, 1993, Vol.31, No.2: 455-464. [J]
[45] C. L. Martinez, X. F. Canovas and M. Chandra. SAR interferometric phase noise reduction using wavelet transform. Electronics Letters, Vol. 37, No. 10, 10th May 2001. [J]
[46] G. Savio, A. Ferretti. PSInSAR Validation by means of a Blind Experiment using Dihedral Reflectors. 2004. [J]
[47] Yue Huanyin, Goo Huadong, Wang Changlin. SAR Interferogram MAP Filtering Based on Stationary Wavelet Transform. IEEE, 2002. [J]
[48] H. Tarayre. 1996. Atmospheric propagation heterogeneities revealed by ERS-1 interferometry. Geophys. 23(9): 989-992. [J]
[49] C.Delacourt, P.Briole, and J.Achache. 1998. Tropospheric corrections of SAR interferograms with strong topography. Application to Etna. Geophys. 25 (15): 2849-2852. [J]
[50] Petar Marinkovic, Gini Ketelaar, Ramon Hanssen. A Controlled ENVISAT/ERS Persistent Experiment, Implications of Corner Reflector Monitoring. 2003. [J]
[51] Teunissen, P.J.G. (1996) GPS carrier phase ambiguity fixing concepts, in GPS for Geodesy, Lecture Notes in Earth Sciences, Springer, pp. 263-335. [J]
[52] Teunissen, P.J.G.(1999).An optimality property of the integer least-squares estimator, Journal of Geodesy (1999) 73: 587-593. [J]
[53] Takako Sakurai-Amano, Joji Iisaka. Speckle Reduction for Small Feature Detection. ACRS 1996. [J]
[54] Takako Sakurai-Amano. Detection of L-band Corner Reflectors in Japanese Residential Environment from JERS-1 SAR imagery. [J]
[55] Ludger Timmen, Xia Ye, Christoph Reigber, Rolf Hartmann, Thomas Fiksel, W. Winzer and Jochen Knoch-Weber , Monitoring of Small Motions in Mining Areas by SAR Interferometry, FRINGE 96.1996. [J]
[56] Xia, Y., Kaufrnann, H. and Xiaofang Guo. Differential SAR Interferometry Using Corner Refletors. IEEE,2002. [J]
[57] Xia, Y, Kaufrnann, H. and Guo, X.F. (2004). Landslide monitoring in the Three Gorges area using D-InSAR and corner reflectors, Photogrammetric Engineering and Remote Sensing, 70(10): 1167-1172. [J]
[58] Zebker, H.A., and R.M. Goldstein, Topographic mapping from interferometric SAR observations, Journal of Geophysical Research, 1986, Vol.91: 4993-4999. [J]
[59] Zebker, H.A., C.L Werner, PA. Rosen, and S. Hensley, Accuracy of topographic maps derived from ERS-1 interferometric radar, IEEE Transactions on Geoscience and Remote Sensing, 1994, Vol.32, No.4: 823-836. [J]
[60] Zebker, H.A., J. Villasenor, Decorrelation in interferometric radar echoes, IEEE Transactions on Geoscience and Remote Sensing, 1992, Vol.30, No.5: 950-959. [J]
[61] Zebker, H. A., P. A. Rosen, and S. Hensley, Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps, Journal of Geophysical Research, 1997 vol.102, No. B4: 7547-7563. [J]
[2]程强.基于永久散射体雷达差分干涉探测区域地表形变的研究.西南交通大学博士学位论文,2006.[D]
[3]刘国祥,丁晓利,陈永奇等.极具潜力的空间对地观测新技术——合成孔径雷达干涉[J]地球科学进展,2000,(06).[J]
[4]刘国祥,丁晓利,李志林.等星载SAR复数图像的配准测绘学报,2001,(01).[J]
[5]刘国祥,丁晓利,陈永奇,等,使用卫星雷达差分干涉技术测量香港赤腊角机场沉降场,2001,Vol.46,No.14:1224-1228[J]
[6]廖明生,林珲.雷达干涉测量学:原理与信号处理基础。测绘出版社,2003.[M]
[7]李陶.重复轨道星载SAR差分干涉监测地表形变研究。武汉大学博士学位论文,2004。[D]
[8]毛建旭,王耀南,夏耶.合成孔径雷达干涉成像技术及其应用。系统工程与电子技术,Vol.25,No.1,2003.[J]
[9]谌华.CRInSAR大气校正模型研究及其初步应用.中国地震局地质研究所硕士学位论文,2006.[D]
[10]宋小刚,李德仁,廖明生等InSAR中大气改正方法的对比研究,测绘科学 Vol21 No.12007.[J]
[11]史世平,使用ERS-1/2干涉测量SAR数据生成DEM,测绘学报,2000,Vol.29,No.4:317-323.[J]
[12]王超,张红,刘智.星载合成孔径雷达干涉测量。北京:科学出版社,2002.[M]
[13]魏子卿,葛茂荣.GPS相对定位的数学模型.测绘出版社,1998.[M]
[14]许才军,王华,黄劲松.GPS与INSAR数据融合研究展望武汉大学学报·信息科学版 Vol.28特刊,2003.5.[J]
[15]张磊.利用Doris计算台湾集集地震位移场及断层滑移量反演.同济大学硕士学位论文,2006.[M]
[16]周春霞.星载SAR干涉测量技术及其在南极冰貌地形研究中的应用,武汉大学博士论文,2004.[D]
[17]Bert M.Kampes and Ramon F.Hanssen.(2004)Ambiguity resolution for Permanent Scatterer Interferometry,IEEE transactions on geoscience and remote Sensing 42(11),2446-2453.[J]
[18]Bevis,M.,S.Businger,T.A.Herring,C.Rocken,R.A.Anthes,and R.H.Ware,GPS meteorology:remote sensing of atmospheric water vapor using the Global Positioning System, Journal of Geophysical Research, 97(D14), 15,787-15,801, 1992. [J]
[19] ESA, http://earth.esa.int [DB/OL]
[20] Ding, X.L., Liu, G.X., Li, Z.W., Li, Z.L., and Chen, Y.Q. Ground subsidence monitoring in Hong Kong with satellite SAR interferometry, Photogrammetric Engineering and Remote Sensing, 70(10): 1151-1156,2004. [J]
[21] Ding, X.L., Li, Z.W., Zheng, D. W., Huang, C. and Zou, W.B. SAR interferogram filtering with 2D Vondrak filter, IEEE Geoscience and Remote Sensing Symposium, Seuol, Korea, Vol. 7, pp4825-4828, July, 2005 . [J]
[22] Ferretti, A., C. Prati, and F. Rocca, Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry, IEEE Transactions on Geoscience and Remote Sensing, 2000, Vol.38, No.5: 2202-2212. [J]
[23] Ferretti A., Prati C, Rocca F. Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, vol. 38, 5:2202-2212,2000 . [J]
[24] Ferretti, A., C. Prati, and F. Rocca, Permanent scatterers in SAR interferometry, IEEE Transactions on Geoscience and Remote Sensing, 2001, Vol.39, No.1: 8-20. [J]
[25] Ferretti A.,Guiliano Savio and Riccardo Barzaghi. Submillimeter Accuracy of InSAR Times Series:Experimental validation on IEEE Transactions on Geoscience and Remote Sensing, Vol, 45, NO5,2007. [J]
[26] Gens, R. and J.L. Van Genderen, SAR interferometry—Issues, techniques, applications, International Journal of Remote Sensing, 1996, Vol. 17, No. 10: 1803-1835. [J]
[27] R. Goldstein. 1995. Atmospheric limitations to repeat-track radar interferometry. Geophys. 22(18):2517-2520. [J]
[28] Hanssen, R., Atmospheric heterogeneities in ERS tandem SAR interferometry, 136 pp., Delft University Press, Delft, the Netherlands, 1998.. [J]
[29] Jos Groot and Matern Often. SAR Imaging of Corner Reflectors Larger Than the Spatial Resolution. IEEE Transactions on Geoscience and Remote Sensing, Vol, 32, NO. 3,1994. [J]
[30] JPL, SRTM home page, http://www.jpl.nasa.gov/srtm/ [DB/OL]
[31] Johan Jacob Mohr and Soren Norvang Madsen. Geometric Calibration of ERS Satellite SAR Images. Ieee Transactions on Geoscience and Remote Sensing, Vol, 39, No. 4, April 2001. [J]
[32] Kampes, B.M. and Usai, S., Doris: the Delft Object-oriented Radar Interferometric Software, 2nd International Symposium on Operationalization of Remote Sensing, Enschede, The Netherlands, 1999. [J]
[33] Kampes, B., Delft Object-oriented Radar Interferometric Software User's manual and technical documentation, http://www.geo.tudelft.nl/doris/, Delft University of Technology . [J] [34] Kampes, B.M (2005=). Displacement Parameter Estimation using Permanent Scatterer Interferometry.PhD thesis. Delft University of technology. [J]
[35] Li, Z.W., Ding, X.L. and Liu, G.X. (2004) Modeling Atmospheric Effects on InSAR with Meteorological and Continuous GPS Observations: Algorithms and Some Test results, Journal of Atmospheric and Solar-Terrestrial Physics, 66: 907-917. [J]
[36] Li, Z.W., Modeling Atmospheric Effect on Repeat-pass InSAR Measurements. The thesis presented for the Degree of Doctor of Philosophy, 2004. [J]
[37] Li, Z.W., Ding, X.L., Chen, Y.Q., Chen W. Assessment of Atmospheric Effects on Repeat-pass InSAR measurements in southern China region, Journal of Geospatial Engineering, 7(1): 1-10,2005. [J]
[38] Li, Z.W., X.L.Ding, C.Huang, GWadge, D.W.Zheng. Modeling of atmospheric effects on InSAR measurements by incorporating terrain elevation information. Journal of Atmospheric and Solar-Terrestrial Physics, 2006. [J]
[39] Li, Z.W., Ding, X.L., Huang, C. and Zheng, D.W. Filtering Method for Radar Interferogram with Strong noise, International Journal of Remote Sensing, 27(14): 2991-3000, 2006. [J]
[40] Liu, G.X., Ding, X.L. et al, Pre- and co-seismic ground deformations of the 1999 Chi-Chi, Taiwan earthquake, measured with SAR interferometry, Computers and Geosciences 2004, 30: 333-343. [J]
[41] Li, Z. (2005). Correction of water vapor effects on repeat-pass InSAR using GPS MODIS and MERIS data. Department of Geomatic Engineering. London, University of London. Doctor of Philosophy. [J]
[42] L. M. Ulander. Accuracy of Using Point Targets for SAR Calibration. LAE, 27:139-148, 1991. [J]
[43] Mark Haynes. Corner reflector aspects of the SNAP program: Demonstrating the utility of differential SAR interferometry for the assessment of earthquake risk. NPA Group, Crockham Park, Edenbridge, Kent TN8 6SR, U.K.2001. [J]
[44] Massonnet, D., and T. Rabaute, Radar interferometry: limits and potential, IEEE Transactions on Geoscience and Remote Sensing, 1993, Vol.31, No.2: 455-464. [J]
[45] C. L. Martinez, X. F. Canovas and M. Chandra. SAR interferometric phase noise reduction using wavelet transform. Electronics Letters, Vol. 37, No. 10, 10th May 2001. [J]
[46] G. Savio, A. Ferretti. PSInSAR Validation by means of a Blind Experiment using Dihedral Reflectors. 2004. [J]
[47] Yue Huanyin, Goo Huadong, Wang Changlin. SAR Interferogram MAP Filtering Based on Stationary Wavelet Transform. IEEE, 2002. [J]
[48] H. Tarayre. 1996. Atmospheric propagation heterogeneities revealed by ERS-1 interferometry. Geophys. 23(9): 989-992. [J]
[49] C.Delacourt, P.Briole, and J.Achache. 1998. Tropospheric corrections of SAR interferograms with strong topography. Application to Etna. Geophys. 25 (15): 2849-2852. [J]
[50] Petar Marinkovic, Gini Ketelaar, Ramon Hanssen. A Controlled ENVISAT/ERS Persistent Experiment, Implications of Corner Reflector Monitoring. 2003. [J]
[51] Teunissen, P.J.G. (1996) GPS carrier phase ambiguity fixing concepts, in GPS for Geodesy, Lecture Notes in Earth Sciences, Springer, pp. 263-335. [J]
[52] Teunissen, P.J.G.(1999).An optimality property of the integer least-squares estimator, Journal of Geodesy (1999) 73: 587-593. [J]
[53] Takako Sakurai-Amano, Joji Iisaka. Speckle Reduction for Small Feature Detection. ACRS 1996. [J]
[54] Takako Sakurai-Amano. Detection of L-band Corner Reflectors in Japanese Residential Environment from JERS-1 SAR imagery. [J]
[55] Ludger Timmen, Xia Ye, Christoph Reigber, Rolf Hartmann, Thomas Fiksel, W. Winzer and Jochen Knoch-Weber , Monitoring of Small Motions in Mining Areas by SAR Interferometry, FRINGE 96.1996. [J]
[56] Xia, Y., Kaufrnann, H. and Xiaofang Guo. Differential SAR Interferometry Using Corner Refletors. IEEE,2002. [J]
[57] Xia, Y, Kaufrnann, H. and Guo, X.F. (2004). Landslide monitoring in the Three Gorges area using D-InSAR and corner reflectors, Photogrammetric Engineering and Remote Sensing, 70(10): 1167-1172. [J]
[58] Zebker, H.A., and R.M. Goldstein, Topographic mapping from interferometric SAR observations, Journal of Geophysical Research, 1986, Vol.91: 4993-4999. [J]
[59] Zebker, H.A., C.L Werner, PA. Rosen, and S. Hensley, Accuracy of topographic maps derived from ERS-1 interferometric radar, IEEE Transactions on Geoscience and Remote Sensing, 1994, Vol.32, No.4: 823-836. [J]
[60] Zebker, H.A., J. Villasenor, Decorrelation in interferometric radar echoes, IEEE Transactions on Geoscience and Remote Sensing, 1992, Vol.30, No.5: 950-959. [J]
[61] Zebker, H. A., P. A. Rosen, and S. Hensley, Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps, Journal of Geophysical Research, 1997 vol.102, No. B4: 7547-7563. [J]