极化干涉合成孔径雷达应用的关键技术研究
|
摘要
极化干涉合成孔径雷达(PolInSAR)是一种先进的SAR系统。由于引入了电磁波的极化方式,极化SAR干涉测量比起传统的干涉测量具有更加广泛的应用。虽然自从11年前第一篇关于极化SAR干涉测量的文章发表以来,国际上很多研究人员在这方面做了大量的工作,但仍存在一些理论与实际问题需要我们去解决。为了推动极化干涉SAR技术的发展,本文专注于其中的一些关键技术,包括图像配准、数据降噪、相位解缠以及树高反演。本文的主要创新点如下。
1)提出了基于相似性参数的极化干涉图像配准方法,利用相干的极化散射矢量的相关系数定义了新的匹配度量,并从理论上分析了方法的性能。实验表明,与仅利用干涉信息的方法相比,新方法提高了像素级和亚像素级配准的稳健性和准确性,减小了误匹配造成的噪声,为获取准确的干涉信息奠定了基础。
2)在利用极化信息对干涉数据进行降噪的问题中,提出了一种基于幅度最优化的方法,通过寻找最优极化通道来优化干涉信号的幅度,从而改善相位质量。建立数学模型并推导出解析解,利用相似性参数做出了合理的物理解释。并讨论了输入为多视数据的情况,扩展为基于强度最优化的方法。实验表明新方法较传统方法在性能上有明显提高,特别在弱信号区域尤为显著。
3)对于干涉数据滤波问题,提出了模糊干涉滤波器和基于幅度最优化的干涉滤波器。两者均考虑了复信号幅度与相位的关系。前者利用邻域信息对弱信号插值增强,并利用加权中值滤波器进行相位滤波。后者则直接将幅度最优化的模型引入,求取最优的滤波器系数。实验表明,两个滤波器在降噪性能上较传统方法均有提高,后者可以利用较小的邻域信息获取更好的输出相位。
4)针对地形起伏剧烈时相位难以精确解缠的问题,提出了基于相位分割和基于参考面的变相位技术。前者将相位解缠视为图像分割问题,将相位合理的分割和拼接,后者则将其视为“去地形效应”,构造参考面来降低解缠的难度。实验表明,两种技术相结合,能够更为准确的恢复复杂地形对应的相位面。
5)对于树高反演问题,提出了一种体相干估计的方法,通过求解干涉复相干的辐角范围,得到了体相干最优估计的近似解析解,提高了树高反演的准确程度。实验验证了该方法较传统估计方法的优越性。
Polarimetric interferometric synthetic aperture radar (PolInSAR) is an advanced SAR system. Since polarizations of electromagnetic waves are employed, polarimetric SAR interferometry has more extensive applications than traditional SAR interferometry. Although some researchers have done much work since the first paper on polarimetric SAR interferometry was published 11 years ago, we still need to solve some problems in theory. For developing the applications of a PolInSAR, this thesis focuses on some key techniques, including image registration, data denoising, phase unwrapping, and tree height estimation. The following innovations are obtained in this thesis.
1) An image registration method for PolInSAR images based on the similarity parameter is proposed: a new registration measurement is defined by the correlation coefficient between the coherent polarimetric scattering vectors, and the method performance is analyzed theoretically. It is proved to have better robustness and accuracy than traditional methods using only interferometric information. The noise caused by mis-registration is reduced and it is beneficial to the later interferogram extraction.
2) A denoising method for InSAR data based on the amplitude- optimization (AO) principle using polarimetric information is proposed. By searching the optimal polarimetric channel to maximize the amplitude of the InSAR signals, the phase between them is improved. The mathematical model is built and solved analytically. A physical explanation is supported by the similarity parameter. As an extension, an intensity-optimization (IO) based method is proposed for multi-look input data. The performance of the proposed method is better than those of the coherence-optimization based methods, especially in weak signal areas.
3) Two filters, the fuzzy filter and the AO based filter, are proposed for InSAR data filtering. Both of them make use of the relationship between the amplitude and phase of the complex signal. In the fuzzy filter, neighborhood information is used to improve weak signals by interpolation, and then the phase is processed by weighted median filter. In the AO based filter, the AO model is introduced to obtain the optimal filter coefficients. They are proved to have better denoising ability than traditional methods. Particularly, the latter filter uses the neighborhood information with the highest efficiency.
4) Two phase-changing techniques, based on the phase segmentation and the referenced surface respectively, are proposed to overcome the difficulty caused by steep topography. The former regards the phase unwrapping as an image segmentation problem, segmenting and combining the phase reasonably. The latter regards it as“topography effect removal”problem, constructing a referenced surface to simplify phase unwrapping. Experiments demonstrate that combining the two techniques can improve the effectiveness and accuracy for complicated topography inversion.
5) In the tree height inversion problem, a volume coherence estimation method is proposed. By considering the argument range of the coherence, an approximate analytical solution of the best volume coherence estimation is obtained. Experimental results show that this method can be used to improve the accuracy of the tree height inversion, demonstrating its advantage over conventional estimation methods.
1)提出了基于相似性参数的极化干涉图像配准方法,利用相干的极化散射矢量的相关系数定义了新的匹配度量,并从理论上分析了方法的性能。实验表明,与仅利用干涉信息的方法相比,新方法提高了像素级和亚像素级配准的稳健性和准确性,减小了误匹配造成的噪声,为获取准确的干涉信息奠定了基础。
2)在利用极化信息对干涉数据进行降噪的问题中,提出了一种基于幅度最优化的方法,通过寻找最优极化通道来优化干涉信号的幅度,从而改善相位质量。建立数学模型并推导出解析解,利用相似性参数做出了合理的物理解释。并讨论了输入为多视数据的情况,扩展为基于强度最优化的方法。实验表明新方法较传统方法在性能上有明显提高,特别在弱信号区域尤为显著。
3)对于干涉数据滤波问题,提出了模糊干涉滤波器和基于幅度最优化的干涉滤波器。两者均考虑了复信号幅度与相位的关系。前者利用邻域信息对弱信号插值增强,并利用加权中值滤波器进行相位滤波。后者则直接将幅度最优化的模型引入,求取最优的滤波器系数。实验表明,两个滤波器在降噪性能上较传统方法均有提高,后者可以利用较小的邻域信息获取更好的输出相位。
4)针对地形起伏剧烈时相位难以精确解缠的问题,提出了基于相位分割和基于参考面的变相位技术。前者将相位解缠视为图像分割问题,将相位合理的分割和拼接,后者则将其视为“去地形效应”,构造参考面来降低解缠的难度。实验表明,两种技术相结合,能够更为准确的恢复复杂地形对应的相位面。
5)对于树高反演问题,提出了一种体相干估计的方法,通过求解干涉复相干的辐角范围,得到了体相干最优估计的近似解析解,提高了树高反演的准确程度。实验验证了该方法较传统估计方法的优越性。
Polarimetric interferometric synthetic aperture radar (PolInSAR) is an advanced SAR system. Since polarizations of electromagnetic waves are employed, polarimetric SAR interferometry has more extensive applications than traditional SAR interferometry. Although some researchers have done much work since the first paper on polarimetric SAR interferometry was published 11 years ago, we still need to solve some problems in theory. For developing the applications of a PolInSAR, this thesis focuses on some key techniques, including image registration, data denoising, phase unwrapping, and tree height estimation. The following innovations are obtained in this thesis.
1) An image registration method for PolInSAR images based on the similarity parameter is proposed: a new registration measurement is defined by the correlation coefficient between the coherent polarimetric scattering vectors, and the method performance is analyzed theoretically. It is proved to have better robustness and accuracy than traditional methods using only interferometric information. The noise caused by mis-registration is reduced and it is beneficial to the later interferogram extraction.
2) A denoising method for InSAR data based on the amplitude- optimization (AO) principle using polarimetric information is proposed. By searching the optimal polarimetric channel to maximize the amplitude of the InSAR signals, the phase between them is improved. The mathematical model is built and solved analytically. A physical explanation is supported by the similarity parameter. As an extension, an intensity-optimization (IO) based method is proposed for multi-look input data. The performance of the proposed method is better than those of the coherence-optimization based methods, especially in weak signal areas.
3) Two filters, the fuzzy filter and the AO based filter, are proposed for InSAR data filtering. Both of them make use of the relationship between the amplitude and phase of the complex signal. In the fuzzy filter, neighborhood information is used to improve weak signals by interpolation, and then the phase is processed by weighted median filter. In the AO based filter, the AO model is introduced to obtain the optimal filter coefficients. They are proved to have better denoising ability than traditional methods. Particularly, the latter filter uses the neighborhood information with the highest efficiency.
4) Two phase-changing techniques, based on the phase segmentation and the referenced surface respectively, are proposed to overcome the difficulty caused by steep topography. The former regards the phase unwrapping as an image segmentation problem, segmenting and combining the phase reasonably. The latter regards it as“topography effect removal”problem, constructing a referenced surface to simplify phase unwrapping. Experiments demonstrate that combining the two techniques can improve the effectiveness and accuracy for complicated topography inversion.
5) In the tree height inversion problem, a volume coherence estimation method is proposed. By considering the argument range of the coherence, an approximate analytical solution of the best volume coherence estimation is obtained. Experimental results show that this method can be used to improve the accuracy of the tree height inversion, demonstrating its advantage over conventional estimation methods.
引文
[1]王超.利用航天飞机成像雷达干涉数据提取数字高程模型.遥感学报, 1997, 1(1): 46-49.
[2] Rogers A E, Ingalls R P. Venus: Mapping the surface reflectivity by radar interferometry. Science, 1969, 65: 797-799.
[3] Zisk S H. A new earth-based radar technique for the measurement of lunar topography. Moon, 1972, 4: 296-300.
[4] Graham L C. Synthetic interferometric radar for topographic mapping. Proceedings of IEEE, 1974, 62: 763-768.
[5] Zebker H A, Goldstein R M. Topographic mapping from interferometric synthetic aperture radar observations. Journal of Geophysical Research, 1986, 91(B5): 4993-4999.
[6] Goldstein R M, Zebker H A, Werner C L. Satellite radar interferometry: Two-demensional phase unwrapping. Radio Science, 1988, 23(4): 713-720.
[7] Li F K, Goldstein R M. Studies of multibaseline spaceorne interferometric synthetic aperture radars. IEEE Transaction on Geoscience and Remote Sensing, 1990, 28(1): 88-96.
[8]李平湘,杨杰.雷达干涉测量原理与应用.测绘出版社, 2006
[9] Rodriguez E, Martin J M. Theory and design of interferometric synthetic aperture radars. IEE Proceedings of Radar and Signal Processing, 1992, 139(2): 147-159
[10] Massonnet D, Rossi M, Carmona C, Adragna F, Peltzer G, Feigl K, Rabaute T. The displacement field of the Landers earthquake mapped by radar interferometry. Nature, 1993, 364: 138-142.
[11] Cloude S R, Papathanassiou K P. Polarimetric SAR Interferometry. IEEE Transactions on Geosciences and Remote Sensing, 1998, 36(5): 1551–1565.
[12] Papathanassiou K P, Reigber A, Scheiber R, Horn R, Moreira A, Cloude S R. Airborne polarimetric SAR interferometry. IGARSS'98, Seattle, WA, USA, 1998, 4: 1901-1903.
[13] Papathanassiou K P. Polarimetric SAR interferometry. PhD Dissertation. DLR, 1999.
[14] Ulbricht A, Papathanassiou K P, Cloude S R. Polarimetric Analysis of SAR-Interferograms in L- and P-Band. IGARSS’98, Seattle, WA, USA, 1998, 3: 1647-1649.
[15] Boerner T. Development of a coherent scattering model for polarimetric SAR interferometry applications. IGARSS’99, Hamburg, Germany, 1999, 2: 1414-1416.
[16] Alberga V and Chandra M. Volume decorrelation resolution in polarimetric SAR interferometry, Electronics Letters, 2003, 39(3): 314-315.
[17] Alberga V, Krogager E. Potential of coherent decompositions in SAR polarimetry and interferometry, IGARSS’04, Anchorage AK, USA, 2004, 3: 1792-1795.
[18]吴一戎,洪文,王彦平.极化干涉SAR的研究现状与启示.电子与信息学报, 2007, 29(5): 1258-1262.
[19]蒋政谚,陈锟山,王志添,高郡汝,李鸿玮.应用ALOS/PALSAR於灾害监测研究.台湾地球科学联合学术研讨会, 2007.
[20]陈思伟,代大海,李盾,王雪松. Radarsat-2的系统组成及技术革新分析.航天电子对抗, 2008, 24(1): 33-36.
[21]陈小英.极化SAR干涉测量地形参数方法研究.硕士论文,中国科学院研究生院(电子学研究所),北京, 2002.
[22]齐海宁.极化干涉SAR测量算法研究.硕士论文,中国科学院研究生院(电子学研究所),北京, 2004.
[23]杨震.合成孔径雷达干涉与极化干涉技术研究.硕士论文,中国科学院研究生院(电子学研究所),北京, 2003.
[24]周勇胜,洪文,王彦平,曹芳,吴一戎.基于RVoG模型的极化干涉SAR最优基线分析.电子学报, 2008, 36(12): 2367-2372.
[25]陈兵,徐绍剑,张平.单基线PolInSAR反演算法研究.电子与信息学报, 2008, 30(7): 1744-1746.
[26]杨震,杨汝良,刘秀清. SAR图像的极化干涉非监督Wishart分类方法和实验研究.电子与信息学报, 2004, 26(5): 752-759.
[27]陈小英,洪峻.极化SAR干涉测量模拟研究.遥感学报, 2002, 6(6): 475-480.
[28]张红. D-InSAR与POLinSAR的方法及应用研究.博士论文,中国科学院研究生院(遥感应用研究所),北京, 2002.
[29]李新武.极化干涉SAR信息提取方法及其应用研究.博士论文,中国科学院研究生院(遥感应用研究所),北京, 2002.
[30]郭华东.航天多波段全极化干涉雷达的地物探测.遥感学报, 1997, 1(1): 32-39.
[31]陈曦,张红,王超.双基线极化干涉合成孔径雷达的植被参数提取.电子与信息学报, 2008, 30(12): 2858-2861.
[32]邹斌,蔡红军,张腊梅,王国喜.森林覆盖下人造目标PolInSAR图象的参数反演模型,宇航学报, 2007, 28(4): 946-951.
[33]邹斌,张腊梅,孙德明,王伟.极化干涉合成孔径雷达图像信息提取技术的进展及未来,电子与信息学报, 2006, 28(10): 1979-1984.
[34]杨磊,赵拥军,王志刚.基于极化合成孔径雷达干涉测量的平均树高提取技术.测绘学报, 2007, 36(2): 163-168.
[35]陈尔学,李增元,庞勇,田昕.基于极化合成孔径雷达干涉测量的平均树高提取技术.林业科学, 2007, 43(4): 66-71.
[36]韦顺军,张晓玲,韩迪.多极化干涉在PolInSAR植被高度估计分析.电子科技大学学报, 2008, 37(S1): 5-8.
[37]周梅,王新鸿,唐伶俐,李传荣.极化干涉合成孔径雷达技术发展与应用.科技导报, 2008, 26(21): 90-93.
[38] Li Zhen, Zhou Jianmin, Tian Bangsen, Xie Chou. The glacier identification using SAR interfermetric and polarimetric information in Qinghai-Tibetan plateau. IGARSS'08, 2008, 4, 1054-1056.
[39] Yang Lei, Zhao Yongjun, Wang Zhigang. Joint phase and power estimation for polarimetric interferometric SAR based on TEL-ESPRIT algorithm. CIE Radar Conference, 2006: 1-4.
[40] Liu D W, Du Y, et al. Analysis of InSAR sensitivity to forest structure based on radar scattering model. Progress In Electromagnetics Research, 2008, PIER 84: 149–171.
[41]于大洋,董贵威,杨健,彭应宁,王超,张红.基于干涉极化SAR数据的森林树高反演.清华大学学报(自然科学版), 2005, 45(3): 334-336.
[42]董贵威,杨健,彭应宁,王超,张红.极化SAR遥感中森林特征探测.清华大学学报(自然科学版), 2003, 43(7): 953-956.
[43] Cloude S R, Papathanassiou K P. Three-stage inversion process for polarimetric SAR interferometry. IEE Proceedings of Radar, Sonar and Navigation, 2003, 150(3): 125- 134.
[44] Lin Yicheng, Sarabandi K. Retrieval of forest parameters using a fractal-based coherent scattering model and a genetic algorithm. IEEE Transactions on Geosciences and Remote Sensing, 1999, 37(3): 1415-1424.
[45] Yamada H, Yanaguchi Y, Rodriguez E, Kim Y, and Boerner W M. Polarimetric SAR Interferometry for Forest canopy analysis by using the super-resolution method. IGARSS’01, Sydney, Australia, 2001, 3: 1101-1103.
[46] Flynn T, Tabb M, Carande R. Direct estimation of vegetation parameters from covariance data in polarimetric SAR Interferometry. IGARSS’02, Tornoto, Canada, 2002, 3: 1908-1910.
[47] Cloude S R, Papathanassiou K P, Reigber A, Boerner W M. Multi-frequency polarimetric SAR interferometry for vegetation structure extraction. IGARSS’00, Honolulu, HI, USA, 2000, 1: 129-131.
[48] Crawford M M, Kumar S, Ricard M R, Gibeaut J C, Neuenschwander A. Fusion of airborne polarimetric and interferometric SAR forclassification of coastal environments. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(3): 1306-1315.
[49] Ferro-Famil L, Pottier E, Lee J S. Classification and interpretation of polarimetric interferometric SAR data. IGARSS’02, Tornoto, Canada, 2002, 1: 635- 637.
[50] Ferro-Famil L, Ponier E, Lee J S. Unsupervised classification and analysis of natural scenes from polarimetric interferometric SAR data. Frontiers of Remote Sensing Information Processing, World Scientific, 2003, 105-139.
[51] Guillaso S, Ferro-Famil L, Reigber A, Pottier E. Building characterization using L-band polarimetric interferometric SAR data. IEEE Geoscience and Remote Sensing Letters, 2005, 2(3), 347- 351.
[52] Garestier F, Dubois-Fernandez P, Dupuis X, Paillou P, Hajnsek I. PolInSAR analysis of X-band data over vegetated and urban areas. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(2): 356- 364.
[53] Sauer S, Ferro-Famil L, Reigber A, Pettier E. Characterisation of buildings using polarimetric interferometric multiple track L-band SAR data. European Radar Conference, Paris, France, 2005, 185-188.
[54] Stebler O, Schwerzmann A, Luthi M, Meier E, Nuesch D. Pol-InSAR observations from an Alpine glacier in the cold infiltration zone at L- and P-band. IEEE Geoscience and Remote Sensing Letters, 2005, 2(3): 357- 361
[55] Hamasaki T, Ferro-Famil L, Pottier E, Sato M. Applications of polarimetric interferometric ground-based SAR (GB-SAR) system to environment monitoring and disaster prevention. European Radar Conference, Paris, France, 2005, 29-32.
[56] Boerner W M, Morisaki J J. From airborne via drones to space-borne polarimetric interferometric SAR environmental stress-change monitoring - comparative assessment of applications, MIKON’04, 2004, 3: 901- 904.
[57] van Zyl J J, Kim Y. The use of polarimetric and interferometric SAR data in floodplain mapping. IGARSS’03, 2003, 1: 443- 445.
[58]王超,张红,刘智.星载合成孔径雷达干涉测量.科学出版社,北京, 2002.
[59] Prati C, Rocca F. Seismic Migration for SAR focusing: interferometrical applications. IEEE Transactions on Geoscience and Remote Sensing, 1990, 28(4): 627-640.
[60] Leong K K, Ee C C, Wang C A H. DTM Generation from 35-day repeat pass ERS-1 interferometry. IGARSS’94, Pasadena, CA, USA, 1994, 4:2288-2290.
[61] Gabriel A K and Goldstein R M. Crossed orbit interferometry: Theory and experimental results from SIR-B. International Journal of Remote Sensing, 1988, 9(5): 857–872.
[62] Lin Qian, Vesecky J F, Zebker H A. Registration of Interferometric Sar Images. IGARSS’92, 1992, 2:1579– 1581.
[63] Fornaro G, Franceschetti G. Image registration in interferometric SAR processing. IEE Proceedings of Radar, Sonar and Navigation, 1995, 142(6): 313-320.
[64] Lee J S, Hoppel K W, Mango S A, Miller A R. Intensity and Phase Statistics of Multilook Polarimetric and Interferometric SAR Imagery. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(5): 1017-1027.
[65] Lopes A, Mougin E, Beaudoin A, Goze S, Nezry E, Touzi R, Karam M A, Fung A K. Phase difference statistics related to sensor and forest parameters. IGARSS’92, Houston, TX, USA, 1992, 779-781.
[66] Martinez C L, Papathanassiou K P, Canovas X F. Polarimetric and interferometric noise modeling, IGARSS'92, Houston, TX, USA, 1992, 835-837.
[67] Eichel P H, Ghiglia D C, Jakowatz Jr C V, Thompson P A, et al. Spotlight SAR Interferometry for Terrain Elevation Mapping and Interferometric Change Detection. Sandia National Labs Tech. Report, 1993, 20(3): 2539-2546.
[68] Lee J S, Papathanassiou K P, Ainsworth T L, Grunes M R, Reigber A. A New Technique for Noise Filtering of SAR Interferometric Phase Images. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(5): 1456-1465.
[69] Trouve E, Caramma M, Maitre H. Fringe detection in noisy complex interferograms. Applied Optics, 1996, 35(20): 3799-3806.
[70] Trouve E, Nicolas J-M, Maitre H. Improving Phase Unwrapping Techniques by the Use of Local Frequency Estimates. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(6): 1963-1972.
[71] Cai Bin, Liang Diannong, Dong Zhen. A New Adaptive Multiresolution Noise-Filtering Approach for SAR Interferometric Phase Images. IEEE Geoscience and Remote Sensing Letters, 2008, 5(2): 266-270.
[72] Meng Dan, Sethu V, Ambikairajah E, Ge Linlin. A Novel Technique for Noise Reduction in InSAR Images. IEEE Geoscience and Remote Sensing Letters, 2007, 4(2): 226-230.
[73] Sagues L, Lopez-Sanchez J M, Fortuny J, et al. Indoor experiments on polarimetric SAR interferometry. IEEE Transactions on Geosciences and Remote Sensing, 2000, 38(2): 671-684.
[74] Colin E, Titin-Schnaider C, Tabbara W. An Interferometric Coherence Optimization Method in Radar Polarimetry for High-Resolution Imagery. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(1): 167-175.
[75] Bai Lu, Wang Yanping, Hong Wen, Peng Hailiang. An Improved Coherence Optimization Method in Polarimetric SAR Interferometry. International Conference on Radar, Shanghai, China, 2006, 1-4.
[76] Lee J S, Grunes M R, Ainsworth T L, Papathanassiou K P, Reigber A. Speckle filtering of SAR data for polarimetric interferometry applications, IGARSS'99, Hamburg, Germany, 1999, 4: 2203-2205.
[77] Lee J S, Cloude S R, Papathanassiou K P, Grunes M R, Woodhouse I H. Speckle filtering and coherence estimation of polarimetric SAR interferometry data for forest applications. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(10): 2254-2263.
[78] Cloude S R, Williams M L. The negative alpha filter a new Processing technique for polarimetric SAR interferometry. IEEE Geoscience and Remote Sensing Letters, 2005, 2(2): 187-191.
[79] Jin Yaqiu, Luo Lin. Terrain topographic inversion using single-pass polarimetric SAR image data. Science in China Series F: Information Sciences, 2004, 47(4): 490-500.
[80] Huntley J M. Noise-immune phase unwrapping algorithm. Applied Optics, 1989, 28(15): 3268-3270.
[81] Cusack R, Huntley J M, Goldrein H T. Improved noise-immune phase unwrapping algorithm. Applied Optics, 1995, 34(5): 781-789.
[82] Buckland J R, Huntley J M, Turner S R E. Unwrapping noisy phase maps by use of a minimum cost matching algorithm. Applied Optics, 1995, 34(23): 5100-5108.
[83] Bone D J. Fourier fringe analysis: the Two-dimensional phase unwrapping problem. Applies Optics, 1991, 30(25): 3627-2632.
[84] Quiroga J A. Gonzalez-Cano A, Bernabeu E. Phase unwrapping algorithm based on an adaptive criterion. Applied Optics, 1995, 34(14): 2560-2563.
[85] Lim H, Xu Wei, Huang Xiaojing. Two new practical methods for phase unwrapping. IGARSS'95, Firenze, Italy, 1995, 1: 196-198.
[86] Derauw D. Phase unwrapping using coherence measurements. Proceedings of SPIE, 1995, 2584: 319-324.
[87] Flynn T J. Consistent 2-D phase unwrapping guided by a quality map. IGARSS'96, Lincoln, NE, USA, 1996, 4: 2057-2059.
[88] Flynn T J. Two-dimensional phase unwrapping with minimum weighted discontinuity. Journal of the Optical Society of America A, 1997, 14(10): 2692-2701.
[89] Xu Wei, Cumming I. A region-growing algorithm for InSAR phase unwrapping. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(1): 124-134.
[90] Liu Sheng, Yang Lianxiang. Regional phase unwrapping method based on fringe estimation and phase map segmentation, SPIE Proceedings, 2007, 46(5): (051012)1-9.
[91]魏志强,金亚秋.基于蚁群算法的InSAR相位解缠算法, 2008, 30(3): 518-523.
[92] Pritt M D, Shipman J S, Syst L F, Gaithersburg M D. Least-squares two-dimensional phase unwrapping using FFT's. IEEE Transactions on Geoscience and Remote sensing, 1994, 32(3): 706-708.
[93] Pritt M D. Multigrid phase unwrapping for interferometric SAR. IGARSS'95, Firenze, Italy, 1995, 1: 562-564.
[94] Pritt M D. Phase unwrapping by means of multigrid techniques for interferometric SAR. IEEE Transactions on Geoscience and Remote Sensing, 1996, 34(3): 728-738.
[95] Ghiglia D C, Romero L A. Robust two-dimensional weighted and unweighted phase unwrapping that uses fast transforms and iterative methods. Journal of the Optical Society of America A, 1994, 11(1): 107-118.
[96] Costantini M. A phase unwrapping method based on network programming. Proceedings of Fringe’96 Workshop, Zurich, Switzerland, 1996, ESA SP-406: 261-272.
[97] Costantini M. A novel phase unwrapping method based on network programming. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(3): 813–821.
[98] Bioucas-Dias J M, Valad?o G. Phase Unwrapping via Graph Cuts. IEEE Transactions on Image Processing, 2007, 16(3): 698-709.
[99] Chen C. Statistical-cost network-flowapproaches to two-dimensional phase unwrapping for radar interferometry. Ph.D. Dissertation, Stanford University, Stanford, CT, USA, 2001.
[100] Treuhaft R N, Madsen S N, Moghaddam M, van Zyl J J. Vegetation characteristics and underlying topography from interferometric radar. Radio Science, 1996, 31(6): 1449-1485, 1996.
[101] Treuhaft R N, Cloude S R. The Structure of Oriented Vegetation from Polarimetric Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(5): 2620-2624.
[102] Treuhaft R N, Siqueira P R. Vertical structure of vegetated land surfaces from interferometric and polarimetric radar. Radio Science, 2000, 35(1): 141-177.
[103] Papathanassiou K P, Cloude S R. Polarimetric effects in repeat-pass SAR interferometry. IGARSS'97, Singapore, Singapore, 1997, 4: 1926-1928.
[104] Cloude S R. Robust parameter estimation using dual baseline polarimetric SAR interferometry. IGARSS'02, Tornoto, Canada, 2002, 2: 838-840.
[105] Papathanassiou K P, Cloude S R. Single-Baseline Polarimetric SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(11): 2352-2363
[106] Lopez-Sanchez J M, Fortuny J, Sieber A J, Sagues L, Bara M, Fabregas X, Broquetas A. Experimental Comparison of Different Scattering Mechanism Selections for Vegetation Height Retrieval by POLINT. IGARSS'00, Honolulu HI, USA, 2000, 1: 138-140.
[107] Stebler O, Meier E, Nuesch D. Forward and inverse modeling of multi-baseline L-band Pol-InSAR E-SAR data. IGARSS'02, Tornoto, Canada, 2002, 2: 823-825.
[108] Tabb M, Flynn T, Carande R. An extended model for characterizing vegetation canopies using polarimetric SAR interferometry. IGARSS'02, Tornoto, Canada, 2002, 2: 1020-1022.
[109] Lin Yicheng, Sarabandi K. A Monte Carlo coherent scattering model for forest canopies usingfractal-generated trees. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(1): 440-451.
[110] IEEE Standard Number 149-1979: Standard Test Procedures 1973, Revision of IEEE Stds. 145-1969, Definitions of Terms for Antennas, Published by the Institute of Electrical and Electronics Engineers, Inc., New York, 1979.
[111] Yang Jian. On Theoretical Problems in Radar Polarimetry. Ph.D. Dissertation, Niigata University, Niigata, Japan, 1999.
[112]庄钊文,肖顺平,王雪松.雷达极化信息处理及其应用.国防工业出版社, 1999.
[113]徐俊毅.极化雷达遥感图像分类研究.博士论文,清华大学,北京, 2002.
[114] Lueneburg E. Principles in radar polarimetry. IEICE Transactions on Communication, 1995, E78-C(10): 1339-1345
[115]廖明生,林珲.雷达干涉测量:原理与信号处理基础.测绘出版社,北京, 2003.
[116]舒宁.雷达影像干涉测量原理.武汉大学出版社,武汉, 2003.
[117] Rosen P A, Hensley S, Joughin I R, Li F K, Madsen S N, Rodriguez E, Goldstein R M. Synthetic Aperture Radar Interferometry. Proceedings of IEEE, 2000, 88(3): 333-382.
[118] Goldstein R M, Zebker H A. Interferometric radar measurement of ocean surface currents. Nature, 1987, 328: 707~709.
[119] Zebker H A, Werner C L, Rosen P A, Hensley S. Accuracy of topographic maps derived from ERS-1 interferometric radar. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(4): 823-836.
[120] Ghiglia D C, Pritt M D. Two-dimensional phase unwrapping: theory, algorithms and software. John Wiley& Sons. Inc, New York, NY, USA, 1998.
[121] Bamler R, Hartl P. Synthetic aperture radar interferometry. Inverse Problems, 1998, 14: 1-54.
[122] Zebker H A, Villasenor J. Decorrelation in interferometric radar echoes. IEEE Transactions on Geoscience and Remote Sensing, 1992, 30(5): 950-959
[123]张克林.干涉合成孔径雷达成像技术研究.硕士论文,北京理工大学,北京, 2004.
[124]郑芳,马德宝,裴怀宁.干涉合成孔径雷达基线估计要素分析.遥感信息, 2005, 3: 7-9.
[125] Just D, Bamler R. Phase statistics of interferograms with applications to synthetic aperture radar, Applied Optics, 1994, 33(20): 4361-4368.
[126] Cloude S R, Papathanassiou K P. Polarimetric optimisation in radar interferometry. Electronics Letters, 1997, 33(13): 1176-1178.
[127]杨清友,王超.干涉雷达复图像配准与干涉纹图的增强.遥感学报, 1999, 3(2), 122-128.
[128] Migliaccio M, Bruno F. A new interpolation kernel for SAR interferometric registration. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(5): 1105–1110.
[129] Keys R G. Cubic convolution interpolation for digital image processing. IEEE Transactions on Acoustics, Speech and Signal Processing, 1981, 29(6): 1153-1160.
[130] Park S K, Schowengerdt R A. Image reconstruction by parametric cubic convolution. Computer Vision, Graph and Image Processing, 1983, 23(3): 258-272.
[131] Yang Jian, Peng Yingning, Lin Shiming. Similarity between two scattering matrices. Electronics Letters, 2001, 37(3): 193-194.
[132] Huynen J R. Phenomenological theory of radar targets. Ph.D. Dissertation, Drukkerij Bronder-Offset NV, 1970.
[133] Candeias A L B, Mura J C, Dutra L V, Moreira J R, Santos P P. Interferogram phase noise reduction using morphological and modified median filters. IGARSS'95, Firenze, Italy, 1995, 1: 166-168.
[134] Lee J S, Ainsworth T L, Grunes M R, Goldstein R M. Noise filtering interferometric SAR images. Proceedings of SPIE, Rome, Italy, 1994, 2315: 735–742.
[135] Touzi R, Lopes A, Bruniquel J, Vachon P W. Coherence estimation for SAR imaginery, IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(1): 135-149.
[136] Guarnieri A M, Prati C. SAR interferometry: A“quick and dirty”coherence estimator for data browsing. IEEE Transactions on Geoscience and Remote Sensing, 1997, 35(3): 660-669
[137] Yang Jian, Yamaguchi Y, Yamada H, Sengoku M, Lin S-M. Stable decomposition of a Mueller matrix. IEICE Transactions on Communication, 1998, E81-B(6): 1261-1268.
[138] Yang Jian, Yamaguchi Y, Yamada H, Sengoku M, Lin S-M. Stable decomposition of a Mueller matrix and extraction of a scattering matrix. Proceedings of ISNIC’98, Tokyo, Japan, 1998, 307-312.
[139] Yang Jian, Peng Yingning, Yamaguchi Y, Yamada H. On modified Huynen’s decomposition of a Kennaugh matrix. IEEE Geoscience and Remote Sensing Letters, 2006, 3(3): 369-372.
[140] Ferretti A, Prati C, Rocca F. Permanent Scatterers in SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(1): 8-20.
[141] Mordeson J N, Nair P S. Fuzzy mathematics: an introduction for engineers and scientists. Heidelberg; New York: Physica-Verlag, 2001.
[142]于大洋.极化SAR在植被地区参数反演中的应用.硕士论文,清华大学,北京, 2004.
[143] Ulaby F T, Moore R K, Fung A K. Microwave remote sensing: active and passive, volumn 3: From theory to applications. Artech House, Norwood, MA, USA, 1986.
[144] Ballester-Berman J D, Lopez-Sanchez J M. Coherence Loci for a Homogeneous Volume Over a Double-Bounce Ground Return. IEEE Geoscience and Remote Sensing Letters, 2007, 4(2): 317-321.
[2] Rogers A E, Ingalls R P. Venus: Mapping the surface reflectivity by radar interferometry. Science, 1969, 65: 797-799.
[3] Zisk S H. A new earth-based radar technique for the measurement of lunar topography. Moon, 1972, 4: 296-300.
[4] Graham L C. Synthetic interferometric radar for topographic mapping. Proceedings of IEEE, 1974, 62: 763-768.
[5] Zebker H A, Goldstein R M. Topographic mapping from interferometric synthetic aperture radar observations. Journal of Geophysical Research, 1986, 91(B5): 4993-4999.
[6] Goldstein R M, Zebker H A, Werner C L. Satellite radar interferometry: Two-demensional phase unwrapping. Radio Science, 1988, 23(4): 713-720.
[7] Li F K, Goldstein R M. Studies of multibaseline spaceorne interferometric synthetic aperture radars. IEEE Transaction on Geoscience and Remote Sensing, 1990, 28(1): 88-96.
[8]李平湘,杨杰.雷达干涉测量原理与应用.测绘出版社, 2006
[9] Rodriguez E, Martin J M. Theory and design of interferometric synthetic aperture radars. IEE Proceedings of Radar and Signal Processing, 1992, 139(2): 147-159
[10] Massonnet D, Rossi M, Carmona C, Adragna F, Peltzer G, Feigl K, Rabaute T. The displacement field of the Landers earthquake mapped by radar interferometry. Nature, 1993, 364: 138-142.
[11] Cloude S R, Papathanassiou K P. Polarimetric SAR Interferometry. IEEE Transactions on Geosciences and Remote Sensing, 1998, 36(5): 1551–1565.
[12] Papathanassiou K P, Reigber A, Scheiber R, Horn R, Moreira A, Cloude S R. Airborne polarimetric SAR interferometry. IGARSS'98, Seattle, WA, USA, 1998, 4: 1901-1903.
[13] Papathanassiou K P. Polarimetric SAR interferometry. PhD Dissertation. DLR, 1999.
[14] Ulbricht A, Papathanassiou K P, Cloude S R. Polarimetric Analysis of SAR-Interferograms in L- and P-Band. IGARSS’98, Seattle, WA, USA, 1998, 3: 1647-1649.
[15] Boerner T. Development of a coherent scattering model for polarimetric SAR interferometry applications. IGARSS’99, Hamburg, Germany, 1999, 2: 1414-1416.
[16] Alberga V and Chandra M. Volume decorrelation resolution in polarimetric SAR interferometry, Electronics Letters, 2003, 39(3): 314-315.
[17] Alberga V, Krogager E. Potential of coherent decompositions in SAR polarimetry and interferometry, IGARSS’04, Anchorage AK, USA, 2004, 3: 1792-1795.
[18]吴一戎,洪文,王彦平.极化干涉SAR的研究现状与启示.电子与信息学报, 2007, 29(5): 1258-1262.
[19]蒋政谚,陈锟山,王志添,高郡汝,李鸿玮.应用ALOS/PALSAR於灾害监测研究.台湾地球科学联合学术研讨会, 2007.
[20]陈思伟,代大海,李盾,王雪松. Radarsat-2的系统组成及技术革新分析.航天电子对抗, 2008, 24(1): 33-36.
[21]陈小英.极化SAR干涉测量地形参数方法研究.硕士论文,中国科学院研究生院(电子学研究所),北京, 2002.
[22]齐海宁.极化干涉SAR测量算法研究.硕士论文,中国科学院研究生院(电子学研究所),北京, 2004.
[23]杨震.合成孔径雷达干涉与极化干涉技术研究.硕士论文,中国科学院研究生院(电子学研究所),北京, 2003.
[24]周勇胜,洪文,王彦平,曹芳,吴一戎.基于RVoG模型的极化干涉SAR最优基线分析.电子学报, 2008, 36(12): 2367-2372.
[25]陈兵,徐绍剑,张平.单基线PolInSAR反演算法研究.电子与信息学报, 2008, 30(7): 1744-1746.
[26]杨震,杨汝良,刘秀清. SAR图像的极化干涉非监督Wishart分类方法和实验研究.电子与信息学报, 2004, 26(5): 752-759.
[27]陈小英,洪峻.极化SAR干涉测量模拟研究.遥感学报, 2002, 6(6): 475-480.
[28]张红. D-InSAR与POLinSAR的方法及应用研究.博士论文,中国科学院研究生院(遥感应用研究所),北京, 2002.
[29]李新武.极化干涉SAR信息提取方法及其应用研究.博士论文,中国科学院研究生院(遥感应用研究所),北京, 2002.
[30]郭华东.航天多波段全极化干涉雷达的地物探测.遥感学报, 1997, 1(1): 32-39.
[31]陈曦,张红,王超.双基线极化干涉合成孔径雷达的植被参数提取.电子与信息学报, 2008, 30(12): 2858-2861.
[32]邹斌,蔡红军,张腊梅,王国喜.森林覆盖下人造目标PolInSAR图象的参数反演模型,宇航学报, 2007, 28(4): 946-951.
[33]邹斌,张腊梅,孙德明,王伟.极化干涉合成孔径雷达图像信息提取技术的进展及未来,电子与信息学报, 2006, 28(10): 1979-1984.
[34]杨磊,赵拥军,王志刚.基于极化合成孔径雷达干涉测量的平均树高提取技术.测绘学报, 2007, 36(2): 163-168.
[35]陈尔学,李增元,庞勇,田昕.基于极化合成孔径雷达干涉测量的平均树高提取技术.林业科学, 2007, 43(4): 66-71.
[36]韦顺军,张晓玲,韩迪.多极化干涉在PolInSAR植被高度估计分析.电子科技大学学报, 2008, 37(S1): 5-8.
[37]周梅,王新鸿,唐伶俐,李传荣.极化干涉合成孔径雷达技术发展与应用.科技导报, 2008, 26(21): 90-93.
[38] Li Zhen, Zhou Jianmin, Tian Bangsen, Xie Chou. The glacier identification using SAR interfermetric and polarimetric information in Qinghai-Tibetan plateau. IGARSS'08, 2008, 4, 1054-1056.
[39] Yang Lei, Zhao Yongjun, Wang Zhigang. Joint phase and power estimation for polarimetric interferometric SAR based on TEL-ESPRIT algorithm. CIE Radar Conference, 2006: 1-4.
[40] Liu D W, Du Y, et al. Analysis of InSAR sensitivity to forest structure based on radar scattering model. Progress In Electromagnetics Research, 2008, PIER 84: 149–171.
[41]于大洋,董贵威,杨健,彭应宁,王超,张红.基于干涉极化SAR数据的森林树高反演.清华大学学报(自然科学版), 2005, 45(3): 334-336.
[42]董贵威,杨健,彭应宁,王超,张红.极化SAR遥感中森林特征探测.清华大学学报(自然科学版), 2003, 43(7): 953-956.
[43] Cloude S R, Papathanassiou K P. Three-stage inversion process for polarimetric SAR interferometry. IEE Proceedings of Radar, Sonar and Navigation, 2003, 150(3): 125- 134.
[44] Lin Yicheng, Sarabandi K. Retrieval of forest parameters using a fractal-based coherent scattering model and a genetic algorithm. IEEE Transactions on Geosciences and Remote Sensing, 1999, 37(3): 1415-1424.
[45] Yamada H, Yanaguchi Y, Rodriguez E, Kim Y, and Boerner W M. Polarimetric SAR Interferometry for Forest canopy analysis by using the super-resolution method. IGARSS’01, Sydney, Australia, 2001, 3: 1101-1103.
[46] Flynn T, Tabb M, Carande R. Direct estimation of vegetation parameters from covariance data in polarimetric SAR Interferometry. IGARSS’02, Tornoto, Canada, 2002, 3: 1908-1910.
[47] Cloude S R, Papathanassiou K P, Reigber A, Boerner W M. Multi-frequency polarimetric SAR interferometry for vegetation structure extraction. IGARSS’00, Honolulu, HI, USA, 2000, 1: 129-131.
[48] Crawford M M, Kumar S, Ricard M R, Gibeaut J C, Neuenschwander A. Fusion of airborne polarimetric and interferometric SAR forclassification of coastal environments. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(3): 1306-1315.
[49] Ferro-Famil L, Pottier E, Lee J S. Classification and interpretation of polarimetric interferometric SAR data. IGARSS’02, Tornoto, Canada, 2002, 1: 635- 637.
[50] Ferro-Famil L, Ponier E, Lee J S. Unsupervised classification and analysis of natural scenes from polarimetric interferometric SAR data. Frontiers of Remote Sensing Information Processing, World Scientific, 2003, 105-139.
[51] Guillaso S, Ferro-Famil L, Reigber A, Pottier E. Building characterization using L-band polarimetric interferometric SAR data. IEEE Geoscience and Remote Sensing Letters, 2005, 2(3), 347- 351.
[52] Garestier F, Dubois-Fernandez P, Dupuis X, Paillou P, Hajnsek I. PolInSAR analysis of X-band data over vegetated and urban areas. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(2): 356- 364.
[53] Sauer S, Ferro-Famil L, Reigber A, Pettier E. Characterisation of buildings using polarimetric interferometric multiple track L-band SAR data. European Radar Conference, Paris, France, 2005, 185-188.
[54] Stebler O, Schwerzmann A, Luthi M, Meier E, Nuesch D. Pol-InSAR observations from an Alpine glacier in the cold infiltration zone at L- and P-band. IEEE Geoscience and Remote Sensing Letters, 2005, 2(3): 357- 361
[55] Hamasaki T, Ferro-Famil L, Pottier E, Sato M. Applications of polarimetric interferometric ground-based SAR (GB-SAR) system to environment monitoring and disaster prevention. European Radar Conference, Paris, France, 2005, 29-32.
[56] Boerner W M, Morisaki J J. From airborne via drones to space-borne polarimetric interferometric SAR environmental stress-change monitoring - comparative assessment of applications, MIKON’04, 2004, 3: 901- 904.
[57] van Zyl J J, Kim Y. The use of polarimetric and interferometric SAR data in floodplain mapping. IGARSS’03, 2003, 1: 443- 445.
[58]王超,张红,刘智.星载合成孔径雷达干涉测量.科学出版社,北京, 2002.
[59] Prati C, Rocca F. Seismic Migration for SAR focusing: interferometrical applications. IEEE Transactions on Geoscience and Remote Sensing, 1990, 28(4): 627-640.
[60] Leong K K, Ee C C, Wang C A H. DTM Generation from 35-day repeat pass ERS-1 interferometry. IGARSS’94, Pasadena, CA, USA, 1994, 4:2288-2290.
[61] Gabriel A K and Goldstein R M. Crossed orbit interferometry: Theory and experimental results from SIR-B. International Journal of Remote Sensing, 1988, 9(5): 857–872.
[62] Lin Qian, Vesecky J F, Zebker H A. Registration of Interferometric Sar Images. IGARSS’92, 1992, 2:1579– 1581.
[63] Fornaro G, Franceschetti G. Image registration in interferometric SAR processing. IEE Proceedings of Radar, Sonar and Navigation, 1995, 142(6): 313-320.
[64] Lee J S, Hoppel K W, Mango S A, Miller A R. Intensity and Phase Statistics of Multilook Polarimetric and Interferometric SAR Imagery. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(5): 1017-1027.
[65] Lopes A, Mougin E, Beaudoin A, Goze S, Nezry E, Touzi R, Karam M A, Fung A K. Phase difference statistics related to sensor and forest parameters. IGARSS’92, Houston, TX, USA, 1992, 779-781.
[66] Martinez C L, Papathanassiou K P, Canovas X F. Polarimetric and interferometric noise modeling, IGARSS'92, Houston, TX, USA, 1992, 835-837.
[67] Eichel P H, Ghiglia D C, Jakowatz Jr C V, Thompson P A, et al. Spotlight SAR Interferometry for Terrain Elevation Mapping and Interferometric Change Detection. Sandia National Labs Tech. Report, 1993, 20(3): 2539-2546.
[68] Lee J S, Papathanassiou K P, Ainsworth T L, Grunes M R, Reigber A. A New Technique for Noise Filtering of SAR Interferometric Phase Images. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(5): 1456-1465.
[69] Trouve E, Caramma M, Maitre H. Fringe detection in noisy complex interferograms. Applied Optics, 1996, 35(20): 3799-3806.
[70] Trouve E, Nicolas J-M, Maitre H. Improving Phase Unwrapping Techniques by the Use of Local Frequency Estimates. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(6): 1963-1972.
[71] Cai Bin, Liang Diannong, Dong Zhen. A New Adaptive Multiresolution Noise-Filtering Approach for SAR Interferometric Phase Images. IEEE Geoscience and Remote Sensing Letters, 2008, 5(2): 266-270.
[72] Meng Dan, Sethu V, Ambikairajah E, Ge Linlin. A Novel Technique for Noise Reduction in InSAR Images. IEEE Geoscience and Remote Sensing Letters, 2007, 4(2): 226-230.
[73] Sagues L, Lopez-Sanchez J M, Fortuny J, et al. Indoor experiments on polarimetric SAR interferometry. IEEE Transactions on Geosciences and Remote Sensing, 2000, 38(2): 671-684.
[74] Colin E, Titin-Schnaider C, Tabbara W. An Interferometric Coherence Optimization Method in Radar Polarimetry for High-Resolution Imagery. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(1): 167-175.
[75] Bai Lu, Wang Yanping, Hong Wen, Peng Hailiang. An Improved Coherence Optimization Method in Polarimetric SAR Interferometry. International Conference on Radar, Shanghai, China, 2006, 1-4.
[76] Lee J S, Grunes M R, Ainsworth T L, Papathanassiou K P, Reigber A. Speckle filtering of SAR data for polarimetric interferometry applications, IGARSS'99, Hamburg, Germany, 1999, 4: 2203-2205.
[77] Lee J S, Cloude S R, Papathanassiou K P, Grunes M R, Woodhouse I H. Speckle filtering and coherence estimation of polarimetric SAR interferometry data for forest applications. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(10): 2254-2263.
[78] Cloude S R, Williams M L. The negative alpha filter a new Processing technique for polarimetric SAR interferometry. IEEE Geoscience and Remote Sensing Letters, 2005, 2(2): 187-191.
[79] Jin Yaqiu, Luo Lin. Terrain topographic inversion using single-pass polarimetric SAR image data. Science in China Series F: Information Sciences, 2004, 47(4): 490-500.
[80] Huntley J M. Noise-immune phase unwrapping algorithm. Applied Optics, 1989, 28(15): 3268-3270.
[81] Cusack R, Huntley J M, Goldrein H T. Improved noise-immune phase unwrapping algorithm. Applied Optics, 1995, 34(5): 781-789.
[82] Buckland J R, Huntley J M, Turner S R E. Unwrapping noisy phase maps by use of a minimum cost matching algorithm. Applied Optics, 1995, 34(23): 5100-5108.
[83] Bone D J. Fourier fringe analysis: the Two-dimensional phase unwrapping problem. Applies Optics, 1991, 30(25): 3627-2632.
[84] Quiroga J A. Gonzalez-Cano A, Bernabeu E. Phase unwrapping algorithm based on an adaptive criterion. Applied Optics, 1995, 34(14): 2560-2563.
[85] Lim H, Xu Wei, Huang Xiaojing. Two new practical methods for phase unwrapping. IGARSS'95, Firenze, Italy, 1995, 1: 196-198.
[86] Derauw D. Phase unwrapping using coherence measurements. Proceedings of SPIE, 1995, 2584: 319-324.
[87] Flynn T J. Consistent 2-D phase unwrapping guided by a quality map. IGARSS'96, Lincoln, NE, USA, 1996, 4: 2057-2059.
[88] Flynn T J. Two-dimensional phase unwrapping with minimum weighted discontinuity. Journal of the Optical Society of America A, 1997, 14(10): 2692-2701.
[89] Xu Wei, Cumming I. A region-growing algorithm for InSAR phase unwrapping. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(1): 124-134.
[90] Liu Sheng, Yang Lianxiang. Regional phase unwrapping method based on fringe estimation and phase map segmentation, SPIE Proceedings, 2007, 46(5): (051012)1-9.
[91]魏志强,金亚秋.基于蚁群算法的InSAR相位解缠算法, 2008, 30(3): 518-523.
[92] Pritt M D, Shipman J S, Syst L F, Gaithersburg M D. Least-squares two-dimensional phase unwrapping using FFT's. IEEE Transactions on Geoscience and Remote sensing, 1994, 32(3): 706-708.
[93] Pritt M D. Multigrid phase unwrapping for interferometric SAR. IGARSS'95, Firenze, Italy, 1995, 1: 562-564.
[94] Pritt M D. Phase unwrapping by means of multigrid techniques for interferometric SAR. IEEE Transactions on Geoscience and Remote Sensing, 1996, 34(3): 728-738.
[95] Ghiglia D C, Romero L A. Robust two-dimensional weighted and unweighted phase unwrapping that uses fast transforms and iterative methods. Journal of the Optical Society of America A, 1994, 11(1): 107-118.
[96] Costantini M. A phase unwrapping method based on network programming. Proceedings of Fringe’96 Workshop, Zurich, Switzerland, 1996, ESA SP-406: 261-272.
[97] Costantini M. A novel phase unwrapping method based on network programming. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(3): 813–821.
[98] Bioucas-Dias J M, Valad?o G. Phase Unwrapping via Graph Cuts. IEEE Transactions on Image Processing, 2007, 16(3): 698-709.
[99] Chen C. Statistical-cost network-flowapproaches to two-dimensional phase unwrapping for radar interferometry. Ph.D. Dissertation, Stanford University, Stanford, CT, USA, 2001.
[100] Treuhaft R N, Madsen S N, Moghaddam M, van Zyl J J. Vegetation characteristics and underlying topography from interferometric radar. Radio Science, 1996, 31(6): 1449-1485, 1996.
[101] Treuhaft R N, Cloude S R. The Structure of Oriented Vegetation from Polarimetric Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(5): 2620-2624.
[102] Treuhaft R N, Siqueira P R. Vertical structure of vegetated land surfaces from interferometric and polarimetric radar. Radio Science, 2000, 35(1): 141-177.
[103] Papathanassiou K P, Cloude S R. Polarimetric effects in repeat-pass SAR interferometry. IGARSS'97, Singapore, Singapore, 1997, 4: 1926-1928.
[104] Cloude S R. Robust parameter estimation using dual baseline polarimetric SAR interferometry. IGARSS'02, Tornoto, Canada, 2002, 2: 838-840.
[105] Papathanassiou K P, Cloude S R. Single-Baseline Polarimetric SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(11): 2352-2363
[106] Lopez-Sanchez J M, Fortuny J, Sieber A J, Sagues L, Bara M, Fabregas X, Broquetas A. Experimental Comparison of Different Scattering Mechanism Selections for Vegetation Height Retrieval by POLINT. IGARSS'00, Honolulu HI, USA, 2000, 1: 138-140.
[107] Stebler O, Meier E, Nuesch D. Forward and inverse modeling of multi-baseline L-band Pol-InSAR E-SAR data. IGARSS'02, Tornoto, Canada, 2002, 2: 823-825.
[108] Tabb M, Flynn T, Carande R. An extended model for characterizing vegetation canopies using polarimetric SAR interferometry. IGARSS'02, Tornoto, Canada, 2002, 2: 1020-1022.
[109] Lin Yicheng, Sarabandi K. A Monte Carlo coherent scattering model for forest canopies usingfractal-generated trees. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(1): 440-451.
[110] IEEE Standard Number 149-1979: Standard Test Procedures 1973, Revision of IEEE Stds. 145-1969, Definitions of Terms for Antennas, Published by the Institute of Electrical and Electronics Engineers, Inc., New York, 1979.
[111] Yang Jian. On Theoretical Problems in Radar Polarimetry. Ph.D. Dissertation, Niigata University, Niigata, Japan, 1999.
[112]庄钊文,肖顺平,王雪松.雷达极化信息处理及其应用.国防工业出版社, 1999.
[113]徐俊毅.极化雷达遥感图像分类研究.博士论文,清华大学,北京, 2002.
[114] Lueneburg E. Principles in radar polarimetry. IEICE Transactions on Communication, 1995, E78-C(10): 1339-1345
[115]廖明生,林珲.雷达干涉测量:原理与信号处理基础.测绘出版社,北京, 2003.
[116]舒宁.雷达影像干涉测量原理.武汉大学出版社,武汉, 2003.
[117] Rosen P A, Hensley S, Joughin I R, Li F K, Madsen S N, Rodriguez E, Goldstein R M. Synthetic Aperture Radar Interferometry. Proceedings of IEEE, 2000, 88(3): 333-382.
[118] Goldstein R M, Zebker H A. Interferometric radar measurement of ocean surface currents. Nature, 1987, 328: 707~709.
[119] Zebker H A, Werner C L, Rosen P A, Hensley S. Accuracy of topographic maps derived from ERS-1 interferometric radar. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(4): 823-836.
[120] Ghiglia D C, Pritt M D. Two-dimensional phase unwrapping: theory, algorithms and software. John Wiley& Sons. Inc, New York, NY, USA, 1998.
[121] Bamler R, Hartl P. Synthetic aperture radar interferometry. Inverse Problems, 1998, 14: 1-54.
[122] Zebker H A, Villasenor J. Decorrelation in interferometric radar echoes. IEEE Transactions on Geoscience and Remote Sensing, 1992, 30(5): 950-959
[123]张克林.干涉合成孔径雷达成像技术研究.硕士论文,北京理工大学,北京, 2004.
[124]郑芳,马德宝,裴怀宁.干涉合成孔径雷达基线估计要素分析.遥感信息, 2005, 3: 7-9.
[125] Just D, Bamler R. Phase statistics of interferograms with applications to synthetic aperture radar, Applied Optics, 1994, 33(20): 4361-4368.
[126] Cloude S R, Papathanassiou K P. Polarimetric optimisation in radar interferometry. Electronics Letters, 1997, 33(13): 1176-1178.
[127]杨清友,王超.干涉雷达复图像配准与干涉纹图的增强.遥感学报, 1999, 3(2), 122-128.
[128] Migliaccio M, Bruno F. A new interpolation kernel for SAR interferometric registration. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(5): 1105–1110.
[129] Keys R G. Cubic convolution interpolation for digital image processing. IEEE Transactions on Acoustics, Speech and Signal Processing, 1981, 29(6): 1153-1160.
[130] Park S K, Schowengerdt R A. Image reconstruction by parametric cubic convolution. Computer Vision, Graph and Image Processing, 1983, 23(3): 258-272.
[131] Yang Jian, Peng Yingning, Lin Shiming. Similarity between two scattering matrices. Electronics Letters, 2001, 37(3): 193-194.
[132] Huynen J R. Phenomenological theory of radar targets. Ph.D. Dissertation, Drukkerij Bronder-Offset NV, 1970.
[133] Candeias A L B, Mura J C, Dutra L V, Moreira J R, Santos P P. Interferogram phase noise reduction using morphological and modified median filters. IGARSS'95, Firenze, Italy, 1995, 1: 166-168.
[134] Lee J S, Ainsworth T L, Grunes M R, Goldstein R M. Noise filtering interferometric SAR images. Proceedings of SPIE, Rome, Italy, 1994, 2315: 735–742.
[135] Touzi R, Lopes A, Bruniquel J, Vachon P W. Coherence estimation for SAR imaginery, IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(1): 135-149.
[136] Guarnieri A M, Prati C. SAR interferometry: A“quick and dirty”coherence estimator for data browsing. IEEE Transactions on Geoscience and Remote Sensing, 1997, 35(3): 660-669
[137] Yang Jian, Yamaguchi Y, Yamada H, Sengoku M, Lin S-M. Stable decomposition of a Mueller matrix. IEICE Transactions on Communication, 1998, E81-B(6): 1261-1268.
[138] Yang Jian, Yamaguchi Y, Yamada H, Sengoku M, Lin S-M. Stable decomposition of a Mueller matrix and extraction of a scattering matrix. Proceedings of ISNIC’98, Tokyo, Japan, 1998, 307-312.
[139] Yang Jian, Peng Yingning, Yamaguchi Y, Yamada H. On modified Huynen’s decomposition of a Kennaugh matrix. IEEE Geoscience and Remote Sensing Letters, 2006, 3(3): 369-372.
[140] Ferretti A, Prati C, Rocca F. Permanent Scatterers in SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(1): 8-20.
[141] Mordeson J N, Nair P S. Fuzzy mathematics: an introduction for engineers and scientists. Heidelberg; New York: Physica-Verlag, 2001.
[142]于大洋.极化SAR在植被地区参数反演中的应用.硕士论文,清华大学,北京, 2004.
[143] Ulaby F T, Moore R K, Fung A K. Microwave remote sensing: active and passive, volumn 3: From theory to applications. Artech House, Norwood, MA, USA, 1986.
[144] Ballester-Berman J D, Lopez-Sanchez J M. Coherence Loci for a Homogeneous Volume Over a Double-Bounce Ground Return. IEEE Geoscience and Remote Sensing Letters, 2007, 4(2): 317-321.