基于GAMMA软件的InSAR相位解缠研究
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摘要
合成孔径雷达干涉测量(InSAR)技术,是以合成孔径雷达的复数据提取的相位信息为信息源来获取地表的三维信息和变化信息的一项新技术,是合成孔径雷达(SAR)卫星应用的一个重要拓展。同传统的遥感技术相比,它具有覆盖面积大,空间分辨率高,高程精度高的优点,并且可以全天时、全天候的工作,是获取三维数字高程模型(DEM)的一种有效方法。合成孔径雷达干涉测量技术已经广泛应用于军事及国民经济的许多领域。正是由于具备这些优势,该技术已经引起了世界各国的重视,成为当前雷达对地观测技术的前沿和研究的热点。
本文分析了InSAR技术的基本原理,介绍了InSAR数据处理的流程,重点研究了相位解缠。相位解缠是InSAR数据处理流程中的关键流程之一,也是主要的误差来源之一。相位解缠的精度直接决定着最后获得的数字高程模型或地表形变结果的精度。能否高效准确的进行相位解缠,已经成为制约InSAR技术发展的一个瓶颈。然而遗憾的是,当前相位解缠的算法虽多,但还没有一种通用的算法。本文对当前国内外的相位解缠算法进行了总结,深入分析了当前相位解缠的几种算法:Goldstein路径积分算法、基于品质图像的路径积算法、掩膜分割算法、Flynn最小非连续算法和最小二乘法,总结了它们各自的优缺点和适用范围。
当前国内研究InSAR相位解缠的文献虽多,但大多都是采用模拟数据,而真实的InSAR数据的处理难度要大的多。本文正是对真实的InSAR数据进行相位解缠实验,采用瑞士的专业雷达遥感数据处理软件GAMMA,成功地对欧空局的ENVISAT-1卫星的ASAR合成孔径雷达传感器所获取的伊朗BAM地区的三景影像数据进行处理,完成了对这三景数据从干涉数据选取到相位解缠的整个流程,最终获得其中两组影像对的相位解缠结果。然后运用MATLAB软件编写程序,读取了GAMMA软件生成的二进制解缠结果,计算出了这两组相位解缠结果的最大值、最小值、均值和方差,绘出了各自的直方图。通过对比二者的这些数据指标、直方图和解缠效率,确定了二者中解缠结果较好的一组,并探讨了造成这种结果的原因。
最后,对本文的研究内容进行了总结,指出了文章的不足之处和以后工作方向,并对InSAR技术在我国的未来进行了展望。
Taking the phase information extracted from the plural data acquired by SAR as its source, Interferometric Synthetic Aperture Radar (InSAR) is developed to obtain the terrain information and variety details. It is also a main profile of satellite SAR application. Compared with traditional remote sensing technique, InSAR has quite a lot of advantages such as large coverage, high spatial resolution, high elevation accuracy, and the capability of working at all time and under all-weather conditions. It is the most effective method to acquire the 3D Digital Elevation Models (DEM). InSAR has evolved to satisfy a variety of applications for both civilian economy and military. This technology has attracted world-wide attention and research.
In this paper,the main principle and data processing flow of InSAR are introduced, especially in phase unwrapping.Phase unwrapping is one of the most important steps of this flow, and also the main source of error. When you want to fetch Digital Elevation Model or the deformation of earth surface, you will find that their precision depends on successful phase unwrapping. Whether or not to do phase unwrapping efficiently and accurately has become a bottleneck of InSAR technological development. Although there are many algorithms, but not a generic algorithm. In this paper, at home and abroad on the current phase unwrapping algorithm is summarized. Branch-cut method, quality quided path following method, mask cut method, Flynn minimum discontinuity and Least square method are discussed in this paper. We Summed up their advantage and disadvantage and scope of application.
The literature about research on InSAR phase unwrapping are numerous at home,but most of them based on simulated data. It more difficult to deal with real data of InSAR. .Using GAMMA software to deal with three scenes of image data in Bam area of Iran, it successfully obtained the results of phase unwrapping about two pairs of image .The data were acquired by Advanced Synthetic Aperture Radar of ESA's ENVISAT-1 satellite. The results of the two groups data about phase unwrapping were compared and analyzed by using MATLAB. It also identified which one is better and the reasons for this result.
Finally, we summed up the research article. The inadequacies and future direction of work of this paper are pointed out. We also prospect the future of InSAR technology in our country.
本文分析了InSAR技术的基本原理,介绍了InSAR数据处理的流程,重点研究了相位解缠。相位解缠是InSAR数据处理流程中的关键流程之一,也是主要的误差来源之一。相位解缠的精度直接决定着最后获得的数字高程模型或地表形变结果的精度。能否高效准确的进行相位解缠,已经成为制约InSAR技术发展的一个瓶颈。然而遗憾的是,当前相位解缠的算法虽多,但还没有一种通用的算法。本文对当前国内外的相位解缠算法进行了总结,深入分析了当前相位解缠的几种算法:Goldstein路径积分算法、基于品质图像的路径积算法、掩膜分割算法、Flynn最小非连续算法和最小二乘法,总结了它们各自的优缺点和适用范围。
当前国内研究InSAR相位解缠的文献虽多,但大多都是采用模拟数据,而真实的InSAR数据的处理难度要大的多。本文正是对真实的InSAR数据进行相位解缠实验,采用瑞士的专业雷达遥感数据处理软件GAMMA,成功地对欧空局的ENVISAT-1卫星的ASAR合成孔径雷达传感器所获取的伊朗BAM地区的三景影像数据进行处理,完成了对这三景数据从干涉数据选取到相位解缠的整个流程,最终获得其中两组影像对的相位解缠结果。然后运用MATLAB软件编写程序,读取了GAMMA软件生成的二进制解缠结果,计算出了这两组相位解缠结果的最大值、最小值、均值和方差,绘出了各自的直方图。通过对比二者的这些数据指标、直方图和解缠效率,确定了二者中解缠结果较好的一组,并探讨了造成这种结果的原因。
最后,对本文的研究内容进行了总结,指出了文章的不足之处和以后工作方向,并对InSAR技术在我国的未来进行了展望。
Taking the phase information extracted from the plural data acquired by SAR as its source, Interferometric Synthetic Aperture Radar (InSAR) is developed to obtain the terrain information and variety details. It is also a main profile of satellite SAR application. Compared with traditional remote sensing technique, InSAR has quite a lot of advantages such as large coverage, high spatial resolution, high elevation accuracy, and the capability of working at all time and under all-weather conditions. It is the most effective method to acquire the 3D Digital Elevation Models (DEM). InSAR has evolved to satisfy a variety of applications for both civilian economy and military. This technology has attracted world-wide attention and research.
In this paper,the main principle and data processing flow of InSAR are introduced, especially in phase unwrapping.Phase unwrapping is one of the most important steps of this flow, and also the main source of error. When you want to fetch Digital Elevation Model or the deformation of earth surface, you will find that their precision depends on successful phase unwrapping. Whether or not to do phase unwrapping efficiently and accurately has become a bottleneck of InSAR technological development. Although there are many algorithms, but not a generic algorithm. In this paper, at home and abroad on the current phase unwrapping algorithm is summarized. Branch-cut method, quality quided path following method, mask cut method, Flynn minimum discontinuity and Least square method are discussed in this paper. We Summed up their advantage and disadvantage and scope of application.
The literature about research on InSAR phase unwrapping are numerous at home,but most of them based on simulated data. It more difficult to deal with real data of InSAR. .Using GAMMA software to deal with three scenes of image data in Bam area of Iran, it successfully obtained the results of phase unwrapping about two pairs of image .The data were acquired by Advanced Synthetic Aperture Radar of ESA's ENVISAT-1 satellite. The results of the two groups data about phase unwrapping were compared and analyzed by using MATLAB. It also identified which one is better and the reasons for this result.
Finally, we summed up the research article. The inadequacies and future direction of work of this paper are pointed out. We also prospect the future of InSAR technology in our country.
引文
[1]廖明生,林珲著.雷达干涉测量[M].北京:测绘出版社,2003.
[2] Klees R and Hanssen R. Basics of synthetic aperture radar interferometry and applications [D ]. NKG Autumn School,2000.
[3]李陶.重复轨道星载SAR差分干涉监测地表形变研究[D].武汉大学博士学位论文,2004.
[4] Kampes B. Delft Object-Oriented Radar Interferometric software user’s manual and technical documentation (V3. 16 )[M ]. Delft University of Technology, 2005.
[5] Goldstein R M, Zebker H A, and Werner C L. Satellite radar interferometry: two-dimensional phase unwrapping[J]. Radio Science, 1988, 23(4): 713—720.
[6] Hanssen R. Rader interferometry: Data interp retation and error analysis[D]. Department of Geodesy, Delft University of Technology, The Netherlands, 2001.
[7] Pritt M D , Shipman J S. Least 2 Squares Two-dimensional Phase Unwrapping Using FFT’S. IEEE Trans[J]. Geosi. Remote Sens, 1994 , 32(3) :706—708.
[8] Bamler R, Adam N, et al. Nosie-induced slope disotrion in 2D phase unwrapping by linear estimators with application to SAR interferometry[J]. IEEE Trans on GRS, May 1998, 36(3): 913—921.
[9] Ghiglia D and Romero L. Robust two-dimensional weighted and unweighted phase unwrapping that uses fast transforms and iterative methods [J]. J. Opt. Soc. Am. A, 1987, 11(1):267—280.
[10] Ghiglia DC , Pritt M.D. Two-Dimensional Phase Unwrapping: Theory , Algorithms, and Software[M]. New York: Wiley, 1998.
[11] Bone D J. Fourier Fringe Analysis: The Two- dimensional Phase Unwrapping Proble .Applied Optics, 1991, 30 :3627—3632 .
[12] Xu W , Cumming I. A region-growing algorit hm for InSAR phase unwrapping. IEEE Trans Geosci Remot Sens , 1999 , 37 ( 3) :124—133.
[13] Flynn TJ . Two dimensional phase unwrapping with minimum weighted discontinuity[J]. Journal of the Optical Society of America A, 1997 , (14) : 2692—2701.
[14] Pritt MD , Shipman J S. Least 2 squares two-dimensional phase unwrapping using FFTs[J]. IEEE Trans Geosci Remote Sens , 1994 ,32 (3) : 706—708.
[15] Fornaro G, Franceshetti G, Lanari R. Interferometric SAR phase unwrapping using Greens formulation[J]. IEEE Trans Geosci Remote Sens , 1996 , 34 (3) : 720—727.
[16] Pritt MD. phase unwrapping by means of multigrid techniques for interferomet ric SAR[J]. IEEE Trans Geosci Remote Sens ,1996 , 34 (3) : 728—738.
[17] Flynn T. J . Consistent 2-D phase unwrapping guided by a quality map [J ] . Proceedings of the 1996 International Geoscience and Remote Sensing Symposium , 1996 , 2057—2059.
[18] Carballo GF , Fieguth PW. Probabilistic cost functions for network flow phase unwrapping[J]. IEEE Trans Geosci Remote Sens , 2000 , 38 (5) : 2192—2201.
[19] Chen CW , Zebker HA. Network approaches to two-dimensional phase unwrapping : Int ractability and two new algorithms[J]. Journal of t he Optical Society of America A , 2000 , 17 (3) : 401—414.
[20] Chen CW , Zebker HA. Two-dimensional phase unwrapping with use of statistical models for cost functions in nonlinear optimization[J]. Journal of the Optical Society of America A , 2001 , 18 (2) :338—351.
[21] Ying L, Frey B, Koetter R, and Munson D C. An iterative dynamic programming approach to 2-D phase unwrapping[J], Proc. IEEE Remote Sensing Symp., Toronto, Canada, June 2002: 469—471.
[22] Zeng QM , Jiao J , Zhang H. A novel hybrid method to unwrapping interferometric phase. Geoscience and Remote Sensing Symposium[J] , IEEE 2004 , 4 (14) : 2632—2635.
[23] Rosen P A, et al. Synthetic aperture radar interferometry[A]. Proceedings of The IEEE[C ]. 2000, 88: 333—381.
[24] Xu F and Jin Y Q. Imaging simulation of polarimetric synthetic aperture radar for comprehensive terrain scene using the mapping and projection algorithm[J]. IEEE Trans. On Geosci. Remote Sensing, 2006, 44(11): 3219—3234.
[25]高勇.干涉SAR的二维相位解缠算法研究[J].地理学与国土研究,2000,16(4):90-96.
[26] Costantini M. A novel phase unwrapping method based on network programming[J]. IEEE Trans. on Geosci. Remote Sensing, 1998, 36(3): 813—821.
[27] Kim S B ,Kim Y S.Least squares phase unwrapping in wavelet domain [J ] . IEEE Proc Vis Image Signal Process ,2005 ,152 (3) :261—267.
[28]赵争,张继贤,张过.遗传算法在InSAR相位解缠中的应用[J].测绘科学,2002,27(3):37—39.
[29]郭春生.优化的区域增长InSAR相位解缠算法[J].中国图形图像学报,2006,11(10):1380—1386.
[30]张莉,彭石宝.贪婪算法在InSAR相位解缠中的应用[J].空军雷达学院学报,2007,21(3):168—171.
[31]程璞,许才军,王华. InSAR相位解缠算法研究[J].大地测量学与地球动力学,2007,27(3):50—55.
[32]于勇,王超,张红,刘智,高鑫.基于不规则网络下网络流算法的相位解缠方法[J].遥感学报,2003,7(6):472—477.
[33]陈家凤.基于多重网格法的相位解缠算法[J].中央民族大学学报(自然科学版),2007,26(2):54—57.
[34]吴友平,彭军还. InSAR相位解缠的半参数解算方法[J].四川测绘,2008,31(1):3—5.
[35]王紫燕,袁运斌.一种组合的InSAR数据的相位解缠算法[J].自然科学进展,2008,18(7):833—835.
[36]魏志强,金亚秋.基于蚁群算法的InSAR相位解缠算法[J].电子与信息学报,2008,30(3):518—523.
[37]李海、廖桂生.基于相关系数加权观测矢量的多基线相位解缠方法[J].自然科学进展,2008,18(3):313-322.
[38]谢捷如,崔海华.基于枝切截断的高质量相位解缠算法[J].南京航空航天大学学报,2008,40(6):799-803.
[39]岑小林,毛建旭.质量图和残差点相结合的InSAR相位解缠方法[J].遥感技术与应用,2008,23(5):556-560.
[40]陈家凤,陈海清.基于小波变换的加权最小二乘相位解缠算法[J].光电子激光,2008,19(4):514—517.
[41]许才军,王华. InSAR相位解缠算法比较及误差分析[ J ].武汉大学学报·信息科学版, 2004, 29 (1) : 67—71.
[42]舒宁编.雷达影像干涉测量原理[M].武汉:武汉大学出版社,2003.
[43]何儒云,王耀南,毛建旭.合成孔径雷达干涉测量( InSAR)关键技术研究[J].测绘工程,2007,16(5):53—56.
[44]于勇.基于网络规划的干涉雷达相位解缠算法研究[D].中国科学研究生院硕士学位论文,2002.
[45]孙占义. InSAR&D-InSAR中相位解缠方法的研究[D].武汉大学硕士学位论文,2003.
[46]刘志铭.干涉合成孔径雷达相位解缠算法的研究[D].解放军信息工程大学硕士学位论文,2004.
[47]刘志栋. InSAR相位解缠方法研究[D].国防科学技术大学硕士学位论文,2005.
[48]吴磊.各种全局最优InSAR相位解缠算法的研究[D].武汉大学硕士学位论文,2005.
[49]付进朋. InSAR相位解缠算法研究[D].西南交通大学硕士学位论文,2006.
[50]段剑华.干涉合成孔径雷达相位解缠算法研究[D].中国地质大学(北京)硕士学位论文,2006.
[51]余君.低相干区的干涉雷达数据处理中滤波与相位解缠方法技术研究[D].浙江大学硕士学位论文,2007.
[52]肖枫. InSAR相位解缠算法的研究[D].同济大学硕士学位论文,2008.
[53]岑小林. InSAR相位解缠算法研究[D].湖南大学硕士学位论文,2008.
[54]王超,张红,刘智著.星载合成孔径雷达干涉测量[M].北京:科学出版社,2002.
[55]瑞士GAMMA公司. GAMMA软件. http://www.gamma-rs.ch/gamma/,2009.
[56]尹占娥著.现代遥感导论[M].北京:科学出版社,2008.
[57]欧空局. EnviView软件. http://envisat.esa.int/services/tools_table.html#envisat/,2009.
[58]欧空局. Descw软件. http://earthnet.esrin.esa.it/, 2009.
[59]于润伟著. MATLAB基础及应用[M].北京:机械工业出版社. 2003.
[60]徐金明编. MATLAB实用教程[M].北京:清华大学出版社. 2005.
[61]葛哲学编.精通MATLAB[M].北京:电子工业出版社. 2008.
[2] Klees R and Hanssen R. Basics of synthetic aperture radar interferometry and applications [D ]. NKG Autumn School,2000.
[3]李陶.重复轨道星载SAR差分干涉监测地表形变研究[D].武汉大学博士学位论文,2004.
[4] Kampes B. Delft Object-Oriented Radar Interferometric software user’s manual and technical documentation (V3. 16 )[M ]. Delft University of Technology, 2005.
[5] Goldstein R M, Zebker H A, and Werner C L. Satellite radar interferometry: two-dimensional phase unwrapping[J]. Radio Science, 1988, 23(4): 713—720.
[6] Hanssen R. Rader interferometry: Data interp retation and error analysis[D]. Department of Geodesy, Delft University of Technology, The Netherlands, 2001.
[7] Pritt M D , Shipman J S. Least 2 Squares Two-dimensional Phase Unwrapping Using FFT’S. IEEE Trans[J]. Geosi. Remote Sens, 1994 , 32(3) :706—708.
[8] Bamler R, Adam N, et al. Nosie-induced slope disotrion in 2D phase unwrapping by linear estimators with application to SAR interferometry[J]. IEEE Trans on GRS, May 1998, 36(3): 913—921.
[9] Ghiglia D and Romero L. Robust two-dimensional weighted and unweighted phase unwrapping that uses fast transforms and iterative methods [J]. J. Opt. Soc. Am. A, 1987, 11(1):267—280.
[10] Ghiglia DC , Pritt M.D. Two-Dimensional Phase Unwrapping: Theory , Algorithms, and Software[M]. New York: Wiley, 1998.
[11] Bone D J. Fourier Fringe Analysis: The Two- dimensional Phase Unwrapping Proble .Applied Optics, 1991, 30 :3627—3632 .
[12] Xu W , Cumming I. A region-growing algorit hm for InSAR phase unwrapping. IEEE Trans Geosci Remot Sens , 1999 , 37 ( 3) :124—133.
[13] Flynn TJ . Two dimensional phase unwrapping with minimum weighted discontinuity[J]. Journal of the Optical Society of America A, 1997 , (14) : 2692—2701.
[14] Pritt MD , Shipman J S. Least 2 squares two-dimensional phase unwrapping using FFTs[J]. IEEE Trans Geosci Remote Sens , 1994 ,32 (3) : 706—708.
[15] Fornaro G, Franceshetti G, Lanari R. Interferometric SAR phase unwrapping using Greens formulation[J]. IEEE Trans Geosci Remote Sens , 1996 , 34 (3) : 720—727.
[16] Pritt MD. phase unwrapping by means of multigrid techniques for interferomet ric SAR[J]. IEEE Trans Geosci Remote Sens ,1996 , 34 (3) : 728—738.
[17] Flynn T. J . Consistent 2-D phase unwrapping guided by a quality map [J ] . Proceedings of the 1996 International Geoscience and Remote Sensing Symposium , 1996 , 2057—2059.
[18] Carballo GF , Fieguth PW. Probabilistic cost functions for network flow phase unwrapping[J]. IEEE Trans Geosci Remote Sens , 2000 , 38 (5) : 2192—2201.
[19] Chen CW , Zebker HA. Network approaches to two-dimensional phase unwrapping : Int ractability and two new algorithms[J]. Journal of t he Optical Society of America A , 2000 , 17 (3) : 401—414.
[20] Chen CW , Zebker HA. Two-dimensional phase unwrapping with use of statistical models for cost functions in nonlinear optimization[J]. Journal of the Optical Society of America A , 2001 , 18 (2) :338—351.
[21] Ying L, Frey B, Koetter R, and Munson D C. An iterative dynamic programming approach to 2-D phase unwrapping[J], Proc. IEEE Remote Sensing Symp., Toronto, Canada, June 2002: 469—471.
[22] Zeng QM , Jiao J , Zhang H. A novel hybrid method to unwrapping interferometric phase. Geoscience and Remote Sensing Symposium[J] , IEEE 2004 , 4 (14) : 2632—2635.
[23] Rosen P A, et al. Synthetic aperture radar interferometry[A]. Proceedings of The IEEE[C ]. 2000, 88: 333—381.
[24] Xu F and Jin Y Q. Imaging simulation of polarimetric synthetic aperture radar for comprehensive terrain scene using the mapping and projection algorithm[J]. IEEE Trans. On Geosci. Remote Sensing, 2006, 44(11): 3219—3234.
[25]高勇.干涉SAR的二维相位解缠算法研究[J].地理学与国土研究,2000,16(4):90-96.
[26] Costantini M. A novel phase unwrapping method based on network programming[J]. IEEE Trans. on Geosci. Remote Sensing, 1998, 36(3): 813—821.
[27] Kim S B ,Kim Y S.Least squares phase unwrapping in wavelet domain [J ] . IEEE Proc Vis Image Signal Process ,2005 ,152 (3) :261—267.
[28]赵争,张继贤,张过.遗传算法在InSAR相位解缠中的应用[J].测绘科学,2002,27(3):37—39.
[29]郭春生.优化的区域增长InSAR相位解缠算法[J].中国图形图像学报,2006,11(10):1380—1386.
[30]张莉,彭石宝.贪婪算法在InSAR相位解缠中的应用[J].空军雷达学院学报,2007,21(3):168—171.
[31]程璞,许才军,王华. InSAR相位解缠算法研究[J].大地测量学与地球动力学,2007,27(3):50—55.
[32]于勇,王超,张红,刘智,高鑫.基于不规则网络下网络流算法的相位解缠方法[J].遥感学报,2003,7(6):472—477.
[33]陈家凤.基于多重网格法的相位解缠算法[J].中央民族大学学报(自然科学版),2007,26(2):54—57.
[34]吴友平,彭军还. InSAR相位解缠的半参数解算方法[J].四川测绘,2008,31(1):3—5.
[35]王紫燕,袁运斌.一种组合的InSAR数据的相位解缠算法[J].自然科学进展,2008,18(7):833—835.
[36]魏志强,金亚秋.基于蚁群算法的InSAR相位解缠算法[J].电子与信息学报,2008,30(3):518—523.
[37]李海、廖桂生.基于相关系数加权观测矢量的多基线相位解缠方法[J].自然科学进展,2008,18(3):313-322.
[38]谢捷如,崔海华.基于枝切截断的高质量相位解缠算法[J].南京航空航天大学学报,2008,40(6):799-803.
[39]岑小林,毛建旭.质量图和残差点相结合的InSAR相位解缠方法[J].遥感技术与应用,2008,23(5):556-560.
[40]陈家凤,陈海清.基于小波变换的加权最小二乘相位解缠算法[J].光电子激光,2008,19(4):514—517.
[41]许才军,王华. InSAR相位解缠算法比较及误差分析[ J ].武汉大学学报·信息科学版, 2004, 29 (1) : 67—71.
[42]舒宁编.雷达影像干涉测量原理[M].武汉:武汉大学出版社,2003.
[43]何儒云,王耀南,毛建旭.合成孔径雷达干涉测量( InSAR)关键技术研究[J].测绘工程,2007,16(5):53—56.
[44]于勇.基于网络规划的干涉雷达相位解缠算法研究[D].中国科学研究生院硕士学位论文,2002.
[45]孙占义. InSAR&D-InSAR中相位解缠方法的研究[D].武汉大学硕士学位论文,2003.
[46]刘志铭.干涉合成孔径雷达相位解缠算法的研究[D].解放军信息工程大学硕士学位论文,2004.
[47]刘志栋. InSAR相位解缠方法研究[D].国防科学技术大学硕士学位论文,2005.
[48]吴磊.各种全局最优InSAR相位解缠算法的研究[D].武汉大学硕士学位论文,2005.
[49]付进朋. InSAR相位解缠算法研究[D].西南交通大学硕士学位论文,2006.
[50]段剑华.干涉合成孔径雷达相位解缠算法研究[D].中国地质大学(北京)硕士学位论文,2006.
[51]余君.低相干区的干涉雷达数据处理中滤波与相位解缠方法技术研究[D].浙江大学硕士学位论文,2007.
[52]肖枫. InSAR相位解缠算法的研究[D].同济大学硕士学位论文,2008.
[53]岑小林. InSAR相位解缠算法研究[D].湖南大学硕士学位论文,2008.
[54]王超,张红,刘智著.星载合成孔径雷达干涉测量[M].北京:科学出版社,2002.
[55]瑞士GAMMA公司. GAMMA软件. http://www.gamma-rs.ch/gamma/,2009.
[56]尹占娥著.现代遥感导论[M].北京:科学出版社,2008.
[57]欧空局. EnviView软件. http://envisat.esa.int/services/tools_table.html#envisat/,2009.
[58]欧空局. Descw软件. http://earthnet.esrin.esa.it/, 2009.
[59]于润伟著. MATLAB基础及应用[M].北京:机械工业出版社. 2003.
[60]徐金明编. MATLAB实用教程[M].北京:清华大学出版社. 2005.
[61]葛哲学编.精通MATLAB[M].北京:电子工业出版社. 2008.
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