极化干涉SAR植被高度估计方法研究
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摘要
极化干涉SAR是将极化信息和干涉技术有效结合,其综合了干涉SAR和极化SAR的优点,通过多通道极化综合技术建立多极化相位干涉的定量关系,可以明显改善干涉相位的信噪比及提高地面高度及参数反演精度。对于多目标复杂场景,极化干涉SAR采用散射矩阵分解技术可以实现多种散射机制相位中心分离及不同干涉相位提取,从而为测量植被覆盖下的地表地形和估计植被高度提供了可能,实现地物各种参数反演,对地面资源和环境监测有重大意义。
本文对极化干涉SAR相关理论以及地面植被高度反演算法进行了研究,所做的主要工作和创新如下:
(1)分析了极化干涉SAR的散射机制特性,对于极化干涉SAR不同极化状态组合进行干涉处理,利用干涉相位分析其对植被区域的敏感性,为地表植被参数反演与估计的极化状态组合选择提供一定依据。
(2)结合SAR图像对信号统计模型,利用子空间投影方法完成两种SAR图像对自适应精配准方法:基于单像素矢量模型的图像精配准算法和基于多像素矢量模型的图像精配准算法,两种方法在一个像素误差情况下仍能得到良好的配准精度,具有良好的稳健性,为极化干涉SAR数据精确地物反演提供了基础。
(3)研究单基线极化干涉SAR地表植被高度反演算法。首先完成了传统的干涉相位差分法和Cloude三阶段算法植被高度反演;然后结合植被体散射模型提出了两种植被高度反演改进算法:基于相干幅度和干涉相位结合反演算法和基于极化干涉SAR数据分布特性的最大似然估计反演算法。相干幅度和干涉相位结合方法反演精度与三阶段反演算法相当,但是运算量大大减小;最大似然估计方法利用数据分布概率函数进行反演,可以获得更好的反演精度结果。通过极化干涉SAR仿真数据和ESAR实测数据试验结果验证了所提反演算法的有效性和优势。
(4)研究双基线极化干涉SAR地表植被高度反演算法。完成了基于相干估计的双基线极化干涉SAR植被高度反演算法,然后提出了一种最大似然估计的双基线极化干涉SAR植被高度反演算法,通过多基线极化干涉SAR仿真数据的参数反演结果与证明该算法的有效性和准确性。
Polarimetric interferometry SAR is new remote sensing technology which combines effectively information of interferometry technology and polarimetric, it comprehensives the all advantages of interferometry SAR and polarization SAR. Through multi-channel polarimetric comprehensive technology and set up the quantitative relationship of the interferometry phase for multi-polarization, polarimetric interferometry SAR can obviously improve the signal-to-noise ratio of interferometry phase and the parameter inversion precision of ground height. For the complicated scene that having many different goals, polarimetric interferometry SAR can separate the interferometry phase center of multiple scattering mechanism and extract different polarimetric interferometry phase by scattering matrix decomposition technique. So polarimetric interferometry SAR provides the possibility for measurement of the surface vegetation cover terrain and estimate vegetation height. By realizing the inversion of various parameters, polarimetric interferometry SAR is of great significance to the ground floor resources and environment monitoring.
In the paper, we studied the basic theories of polarimetric interferometry SAR and inversion algorithms of ground vegetation height. This paper mainly work and innovation of are as follows:
(1) First, we analysis the characteristics of the scattering mechanism for polarimetric interferometry SAR. For the different polarimetric interferometry phase of polarimetric interferometry SAR, we analysis of their sensitivity for vegetation regional using the interferometry phase. The characteristics of different sensitivity provides certain basis for the polarization state combination selection to vegetation parameter inversion and estimate.
(2) Based on subspace projection method ,we completed the adaptive SAR images registration algorithm. Combined with the statistical model of interferometry SAR, we using signal subspace projection method to finish two SAR image adaptive refined registration method: adaptive SAR image registration algorithm based on the combination of single pixel model and adaptive image registration algorithm based on pure flat terrain model. both method can get good registration precision even if in a pixel error conditions. So the two adaptive SAR images registration algorithm have good robustness.
(3) Some vegetation parameter inversion algorithms are researched in single-baseline polarimetric interferometry SAR. First, we finish the traditional interferometry phase difference method for vegetation height inversion and the Cloude three stage method for vegetation height inversion. Combined with the vegetation volume scattering modal we presented two vegetation height inversion methods: based on coherent amplitude and phase vegetation height inversion algorithm and based on maximum likelihood estimation inversion algorithm for polarimetric interferometry SAR data distribution.
(4) Finaly, we Study some vegetation parameter inversion algorithms of double-baseline polarimetric interferometry SAR. First we finished polarimetric coherent estimate method for double-baseline polarimetric interferometry SAR vegetation height inversion algorithm, and then proposes a maximum likelihood estimation of double-baseline polarimetric interferometry SAR vegetation height inversion algorithm.
本文对极化干涉SAR相关理论以及地面植被高度反演算法进行了研究,所做的主要工作和创新如下:
(1)分析了极化干涉SAR的散射机制特性,对于极化干涉SAR不同极化状态组合进行干涉处理,利用干涉相位分析其对植被区域的敏感性,为地表植被参数反演与估计的极化状态组合选择提供一定依据。
(2)结合SAR图像对信号统计模型,利用子空间投影方法完成两种SAR图像对自适应精配准方法:基于单像素矢量模型的图像精配准算法和基于多像素矢量模型的图像精配准算法,两种方法在一个像素误差情况下仍能得到良好的配准精度,具有良好的稳健性,为极化干涉SAR数据精确地物反演提供了基础。
(3)研究单基线极化干涉SAR地表植被高度反演算法。首先完成了传统的干涉相位差分法和Cloude三阶段算法植被高度反演;然后结合植被体散射模型提出了两种植被高度反演改进算法:基于相干幅度和干涉相位结合反演算法和基于极化干涉SAR数据分布特性的最大似然估计反演算法。相干幅度和干涉相位结合方法反演精度与三阶段反演算法相当,但是运算量大大减小;最大似然估计方法利用数据分布概率函数进行反演,可以获得更好的反演精度结果。通过极化干涉SAR仿真数据和ESAR实测数据试验结果验证了所提反演算法的有效性和优势。
(4)研究双基线极化干涉SAR地表植被高度反演算法。完成了基于相干估计的双基线极化干涉SAR植被高度反演算法,然后提出了一种最大似然估计的双基线极化干涉SAR植被高度反演算法,通过多基线极化干涉SAR仿真数据的参数反演结果与证明该算法的有效性和准确性。
Polarimetric interferometry SAR is new remote sensing technology which combines effectively information of interferometry technology and polarimetric, it comprehensives the all advantages of interferometry SAR and polarization SAR. Through multi-channel polarimetric comprehensive technology and set up the quantitative relationship of the interferometry phase for multi-polarization, polarimetric interferometry SAR can obviously improve the signal-to-noise ratio of interferometry phase and the parameter inversion precision of ground height. For the complicated scene that having many different goals, polarimetric interferometry SAR can separate the interferometry phase center of multiple scattering mechanism and extract different polarimetric interferometry phase by scattering matrix decomposition technique. So polarimetric interferometry SAR provides the possibility for measurement of the surface vegetation cover terrain and estimate vegetation height. By realizing the inversion of various parameters, polarimetric interferometry SAR is of great significance to the ground floor resources and environment monitoring.
In the paper, we studied the basic theories of polarimetric interferometry SAR and inversion algorithms of ground vegetation height. This paper mainly work and innovation of are as follows:
(1) First, we analysis the characteristics of the scattering mechanism for polarimetric interferometry SAR. For the different polarimetric interferometry phase of polarimetric interferometry SAR, we analysis of their sensitivity for vegetation regional using the interferometry phase. The characteristics of different sensitivity provides certain basis for the polarization state combination selection to vegetation parameter inversion and estimate.
(2) Based on subspace projection method ,we completed the adaptive SAR images registration algorithm. Combined with the statistical model of interferometry SAR, we using signal subspace projection method to finish two SAR image adaptive refined registration method: adaptive SAR image registration algorithm based on the combination of single pixel model and adaptive image registration algorithm based on pure flat terrain model. both method can get good registration precision even if in a pixel error conditions. So the two adaptive SAR images registration algorithm have good robustness.
(3) Some vegetation parameter inversion algorithms are researched in single-baseline polarimetric interferometry SAR. First, we finish the traditional interferometry phase difference method for vegetation height inversion and the Cloude three stage method for vegetation height inversion. Combined with the vegetation volume scattering modal we presented two vegetation height inversion methods: based on coherent amplitude and phase vegetation height inversion algorithm and based on maximum likelihood estimation inversion algorithm for polarimetric interferometry SAR data distribution.
(4) Finaly, we Study some vegetation parameter inversion algorithms of double-baseline polarimetric interferometry SAR. First we finished polarimetric coherent estimate method for double-baseline polarimetric interferometry SAR vegetation height inversion algorithm, and then proposes a maximum likelihood estimation of double-baseline polarimetric interferometry SAR vegetation height inversion algorithm.
引文
[1] S. R. Cloude, K. P. Papathanassiou. Polarimetric SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(5):1551-1565
[2] K. P. Papathanassiou, A. Reigber, R. Scheiber, R. Horn, A. Moreira, S. R Cloude. Airborne Polarimetric SAR Interferometry. Proceedings of IEEE Symposium on Geoscience and Remote Sensing1998(IGARSS1998) , Seattle USA, July 1998
[3] K. P. Papathanassiou, A. Reiger, S. R. Cloude. Vegetation and Ground Parameter Estimation using Polarimetric Interferometry Part I: The Role of Polarisation. Part II: Parameter Inversion and Optimal Polarisations. Proceedings of the CEOS SAR Workshop, Toulouse, Oct 1999:347-358
[4] S. R. Cloude, K. P. Papathanssiou, W. M. Boerner. A Fast Method for Vegetation Correction in Topographic Mapping Using Polarimetric Radar Interferometry. Proceedings of 3rd European SAR Conference EUSAR 2000, Munich, Germany, May 2000:261-264
[5] S. R. Cloude, K. P. Papathanassiou, W.M.Boerner. The Remote Sensing of Oriented Volume Scattering Using Polarimetric Radar Interferometry. Proceedings of International Symposium on Antennas and Propagation 2000, Fukuoka, Japan, August 2000:549-552
[6] K. P. Papathanassiou, S. R. Cloude. Single baseline Polarimetric SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 2001,39(11):2352-2363
[7] S. R. Cloude. Radar Polarimetry and Interferometry: A Tutorial Introduction. IEEE Geoscience and Remote Sensing Newsletter, June 2004
[8] J. S. Lee, S. R. Cloude, K. P. Papathanassiou, M. R. Grunes, I. H. Woodhouse. Speckle Filtering and Coherence Estimation of POLInSAR Data for Forest Applications. IEEE Transactions on Geoscience and Remote Sensing, October 2003, 41(10):2254-2263
[9] M. Qong. Coherence optimization using the polarization state conformation in PolInSAR. IEEE Trans on Geoscience and Remote Sensing Letters, July 2005,2(3):301-305
[10] M. Qong. Polarization State Conformation and its Application to Change Detection in Po1SAR. IEEE GRSL, Oct 2004, 1(4):304-308
[11] M. Qong. A New Polarization State Conformation and its Application to Coherence Optimization in PoIInSAR. Proceedings of IEEE Symposium on Geoscience and RemoteSensing2004, Anchorage ,Alaska, Sept 2004:2495-2498
[12] J. Dall, K. P. Papathanassiou, H. Skriver. Polarimetric SAR Interferometry Applied to Land Ice: First Results. proceedings of IEEE Geoscience and Remote Sensing Symposium(IGARSS 2003), Toulouse, France, 2003:1432-1434
[13] H. Yamada, Y. Yamaguchi, E. Rodriguez, Y. Kim, W. M. Boerner. Polarimetric SAR Interferometry for forest Canopy Analysis by using the Super-Resolution Method. Processing of International Geoscience and Remote Sensing Symposium 2001(IGARSS01), 2001(3):1101-1103
[14] J. M. Lopez-Sanchez, J. D. Ballester-Berman, Y. Marquez-Moreno. Model Limitations and Parameter-Estimation Methods for Agricultural Applications of Polarimetric SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, November 2007, 45(11):3481-3493
[15] M. J?ger, M. Neumann, S. Guillaso, A. Reigber. A Self-Initializing PolInSAR Classifier Using Interferometric Phase Differences. IEEE Transactions on Geoscience and Remote Sensing, Novenber 2007, 45(11):3053-3517
[16] H. Yamada, H. Okada, Y. Yamaguchi. Accuracy Improvement of ESPRIT based Polarimetric SAR Interferometry for Forest Height Estimation. Proceedings of IEEE Symposium on Geoscience and Remote Sensing2005, July 2005:4077-4080
[17] S. Guillaso, L. F. Famil, A. Reigber, E. Pottier. Building characterization using L-band polarimetric interferometric SAR data. IEEE Transactions on Geoscience and Remote Sensing Letters, July 2005, 3(2):347-351
[18] R. Z. Schneider, K. P. Papathanassiou, I. hajnsek, A. Moreira. Polarimetric Interferometry over Urban Areas: Information Extraction using Coherence Scatterers. Proceedings of IEEE International Geoscience and Remote Sensing Symposium(IGARSS 2005) , Seoul, Korea, July 2005
[19] F. Garestier, P. D. Fernandez, X.. Dupuis, P. Paillou, I. Hajnsek. PolInSAR Analysis of X-Band Data Over Vegetated and Urban Areas. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(2):356-364.
[20] G. Margarit, J. Mallorquí, X. Fàbregas. Single-Pass Polarimetric SAR Interferometryfor Vessel Classification. IEEE Transactions on Geoscience and Remote Sensing, November 2007, 45(11):3494-3502
[21]李新武,郭华东,等.航天飞机极化干涉雷达数据反演地表植被参数.遥感学报,2002,6(6):424-429
[22]李新武,郭华东,李震,王长林.用SIR-C航天飞机双频极化干涉雷达估计植被高度的方法研究.高技术通讯,2005,15(7):79-84
[23]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
[24]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):66-70
[25]陈兵,徐绍剑,张平.单基线PolInSAR反演算法研究.电子信息学报,2008,30(7):1744-1746
[26]王超,张红,刘智.星载合成孔径雷达干涉测量.科学出版社,2002
[27]郭华东,李新武.极化干涉雷达遥感机制及应用.遥感学报,2002,6(6):401-405
[28] E. Colin, C. Titin-Schnaider, W. Tabbara. An interferometric coherence optimization method in radar polarimetry for high-resolution imagery. IEEE Trans Geosci Remote Sens, Jan.2006, 44(1):167-175
[29] J. L. Gomez-Dans, S. Quegan. Constraint coherence optimization in polarimetric interferometry of layered targets. Proc POLINSAR, Frascati, Italy, Jan. 2005
[30] M. Qong. Coherence optimization using the polarization state conformation PolInSAR. IEEE Geosci Remote Sens Lett, Jul.2005, 2(3):301–305
[31]戴博伟.多极化合成孔径雷达系统与极化信息处理研究:[博士学位论文].2000
[32] E. Pottier, L. Ferro-Famil, S. Allain, S. Cloude, etc. POLSARPRO V3.3: the educational toolbox for Polarimetric and interferpmetry SAR data processing. Proceedings of IEEE Geoscience and Remote Sensing Symposium2008
[33]皮亦鸣,杨建宇,付毓生,杨晓波.合成孔径雷达成像原理.电子科大学出版社,2007
[34]李海,李真芳,廖桂生.InSAR干涉相位图生成的图像配准自补偿方法.中国科学(E辑),2006,36(2):191-201
[35] Li ZF, Bao Z, Li H. Image auto-Coregistration and InSAR interferogram estimation using joint subspace Projection. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(2):288-297
[36]李海,廖桂生.基于广义导向矢量模型的InSAR干涉相位估计方法.自然科学进展,2007, 17(11):1555-1564
[37] R. N. Treuhaft, S. N. Madsen, M. Moghaddam, J. J. van Zyl. VegetationCharacteristics and Surface Topography from Interferometric Radar.Radio Science, 1996, 31:14491485
[38] R. N. Treuhaft, S. R. Cloude. The Structure of Oriented Vegetation from Polarimetric Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(5):2620-2624
[39] R. N. Treuhaft. Vertical Structure of Vegetated Land Surfaces from Interferometric and Polarimetric Radar. Radio Sciences, 2000, 35(1):141-177
[40] H. Yamada, Y. Yamaguchi, E. Rodriguez, Y. Kim, W. M.Boerner. Polarimetric SAR Interferometry for Forest Canopy Analysis by Using the Super-resolution Method. IEICE Transactions on Electronics, December 2001, 84(12):1917-1924
[41] E. Colin, C. Titin-Schneider, W. Tabbara. Investigation of Different Interferometric Coherence Optimisation Methods. Proceedings of ESA Workshop on Applications of SAR Polarimetry and Polarimetric Interferometry(POLInSAR 03) , January 2003
[42] S. R. Cloude, K. P. Papathanssiou, A. Reigber. Polarimetric SAR Interferometry at P Band for Vegetation Structure Extraction. Proceedings of European SAR Conference EUSAR 2000, Munich, Germany, May 2000:249-252
[43] K. P. Papathanassiou, S. R. Cloude, A. Reigber. Single and Multi-Baseline Polarimetric SAR Interferometry over Forested Terrain. Proceedings of European SAR Conference EUSAR 2000, Munich, Germany, May 2000:123-126
[44]张腊梅.L波段PoIInSAR图像地表参数反演方法研究:[硕士学位论文].2006,哈尔滨工业大学
[45] S. R. Cloude, K. P. Papathanassiou. A 3-Stage Inversion Process for Polarimetric SAR Interferometry. Proc of EUSAR2002, Cologne, Germany, June 2002:297-282
[46] S R. Cloude, K. P. Papathanassiou. Three-stage Inversion Process for Polarimetric SAR Interferometry. IEE Proc Radar Sonar Navig, 2003, 150(3):125-134
[47] M. Tabb, R. Carande. Robust Inversion of Vegetation Structure Parameters from Low Frequency Polarimetric Interferometric SAR. Proceedings of IEEE International Geoscience and Remote Sensing Symposium(IGARSS 2001), Sydney, Australia, July 2001
[48] M. Tabb, T. Flynn, R. Carande. Direct Estimation of Vegetation Parameters from Covariance Data in POLINSAR. Proceedings of IGARSS 2002, Toronto, Canada, 2002
[49] S. R. Cloude. Robust Parameter Estimation Using DualBaseline Polarimetric SAR Interferometry, Processing of International Geoscience and Remote Sensing Symposium 2002, 2002
[50] S. R. Cloude, M. L. Williams. A Coherent EM Scattering Model for Dual Baseline POLInSAR, Processing of International Geoscience and Remote Sensing Symposium 2003, 2003
[51] S. R. Cloude. Dual-Baseline Coherence Tomography. IEEE Transactions on Geoscience and Remote Sensing, 2007, 4(1):127-131
[2] K. P. Papathanassiou, A. Reigber, R. Scheiber, R. Horn, A. Moreira, S. R Cloude. Airborne Polarimetric SAR Interferometry. Proceedings of IEEE Symposium on Geoscience and Remote Sensing1998(IGARSS1998) , Seattle USA, July 1998
[3] K. P. Papathanassiou, A. Reiger, S. R. Cloude. Vegetation and Ground Parameter Estimation using Polarimetric Interferometry Part I: The Role of Polarisation. Part II: Parameter Inversion and Optimal Polarisations. Proceedings of the CEOS SAR Workshop, Toulouse, Oct 1999:347-358
[4] S. R. Cloude, K. P. Papathanssiou, W. M. Boerner. A Fast Method for Vegetation Correction in Topographic Mapping Using Polarimetric Radar Interferometry. Proceedings of 3rd European SAR Conference EUSAR 2000, Munich, Germany, May 2000:261-264
[5] S. R. Cloude, K. P. Papathanassiou, W.M.Boerner. The Remote Sensing of Oriented Volume Scattering Using Polarimetric Radar Interferometry. Proceedings of International Symposium on Antennas and Propagation 2000, Fukuoka, Japan, August 2000:549-552
[6] K. P. Papathanassiou, S. R. Cloude. Single baseline Polarimetric SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 2001,39(11):2352-2363
[7] S. R. Cloude. Radar Polarimetry and Interferometry: A Tutorial Introduction. IEEE Geoscience and Remote Sensing Newsletter, June 2004
[8] J. S. Lee, S. R. Cloude, K. P. Papathanassiou, M. R. Grunes, I. H. Woodhouse. Speckle Filtering and Coherence Estimation of POLInSAR Data for Forest Applications. IEEE Transactions on Geoscience and Remote Sensing, October 2003, 41(10):2254-2263
[9] M. Qong. Coherence optimization using the polarization state conformation in PolInSAR. IEEE Trans on Geoscience and Remote Sensing Letters, July 2005,2(3):301-305
[10] M. Qong. Polarization State Conformation and its Application to Change Detection in Po1SAR. IEEE GRSL, Oct 2004, 1(4):304-308
[11] M. Qong. A New Polarization State Conformation and its Application to Coherence Optimization in PoIInSAR. Proceedings of IEEE Symposium on Geoscience and RemoteSensing2004, Anchorage ,Alaska, Sept 2004:2495-2498
[12] J. Dall, K. P. Papathanassiou, H. Skriver. Polarimetric SAR Interferometry Applied to Land Ice: First Results. proceedings of IEEE Geoscience and Remote Sensing Symposium(IGARSS 2003), Toulouse, France, 2003:1432-1434
[13] H. Yamada, Y. Yamaguchi, E. Rodriguez, Y. Kim, W. M. Boerner. Polarimetric SAR Interferometry for forest Canopy Analysis by using the Super-Resolution Method. Processing of International Geoscience and Remote Sensing Symposium 2001(IGARSS01), 2001(3):1101-1103
[14] J. M. Lopez-Sanchez, J. D. Ballester-Berman, Y. Marquez-Moreno. Model Limitations and Parameter-Estimation Methods for Agricultural Applications of Polarimetric SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, November 2007, 45(11):3481-3493
[15] M. J?ger, M. Neumann, S. Guillaso, A. Reigber. A Self-Initializing PolInSAR Classifier Using Interferometric Phase Differences. IEEE Transactions on Geoscience and Remote Sensing, Novenber 2007, 45(11):3053-3517
[16] H. Yamada, H. Okada, Y. Yamaguchi. Accuracy Improvement of ESPRIT based Polarimetric SAR Interferometry for Forest Height Estimation. Proceedings of IEEE Symposium on Geoscience and Remote Sensing2005, July 2005:4077-4080
[17] S. Guillaso, L. F. Famil, A. Reigber, E. Pottier. Building characterization using L-band polarimetric interferometric SAR data. IEEE Transactions on Geoscience and Remote Sensing Letters, July 2005, 3(2):347-351
[18] R. Z. Schneider, K. P. Papathanassiou, I. hajnsek, A. Moreira. Polarimetric Interferometry over Urban Areas: Information Extraction using Coherence Scatterers. Proceedings of IEEE International Geoscience and Remote Sensing Symposium(IGARSS 2005) , Seoul, Korea, July 2005
[19] F. Garestier, P. D. Fernandez, X.. Dupuis, P. Paillou, I. Hajnsek. PolInSAR Analysis of X-Band Data Over Vegetated and Urban Areas. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(2):356-364.
[20] G. Margarit, J. Mallorquí, X. Fàbregas. Single-Pass Polarimetric SAR Interferometryfor Vessel Classification. IEEE Transactions on Geoscience and Remote Sensing, November 2007, 45(11):3494-3502
[21]李新武,郭华东,等.航天飞机极化干涉雷达数据反演地表植被参数.遥感学报,2002,6(6):424-429
[22]李新武,郭华东,李震,王长林.用SIR-C航天飞机双频极化干涉雷达估计植被高度的方法研究.高技术通讯,2005,15(7):79-84
[23]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
[24]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):66-70
[25]陈兵,徐绍剑,张平.单基线PolInSAR反演算法研究.电子信息学报,2008,30(7):1744-1746
[26]王超,张红,刘智.星载合成孔径雷达干涉测量.科学出版社,2002
[27]郭华东,李新武.极化干涉雷达遥感机制及应用.遥感学报,2002,6(6):401-405
[28] E. Colin, C. Titin-Schnaider, W. Tabbara. An interferometric coherence optimization method in radar polarimetry for high-resolution imagery. IEEE Trans Geosci Remote Sens, Jan.2006, 44(1):167-175
[29] J. L. Gomez-Dans, S. Quegan. Constraint coherence optimization in polarimetric interferometry of layered targets. Proc POLINSAR, Frascati, Italy, Jan. 2005
[30] M. Qong. Coherence optimization using the polarization state conformation PolInSAR. IEEE Geosci Remote Sens Lett, Jul.2005, 2(3):301–305
[31]戴博伟.多极化合成孔径雷达系统与极化信息处理研究:[博士学位论文].2000
[32] E. Pottier, L. Ferro-Famil, S. Allain, S. Cloude, etc. POLSARPRO V3.3: the educational toolbox for Polarimetric and interferpmetry SAR data processing. Proceedings of IEEE Geoscience and Remote Sensing Symposium2008
[33]皮亦鸣,杨建宇,付毓生,杨晓波.合成孔径雷达成像原理.电子科大学出版社,2007
[34]李海,李真芳,廖桂生.InSAR干涉相位图生成的图像配准自补偿方法.中国科学(E辑),2006,36(2):191-201
[35] Li ZF, Bao Z, Li H. Image auto-Coregistration and InSAR interferogram estimation using joint subspace Projection. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(2):288-297
[36]李海,廖桂生.基于广义导向矢量模型的InSAR干涉相位估计方法.自然科学进展,2007, 17(11):1555-1564
[37] R. N. Treuhaft, S. N. Madsen, M. Moghaddam, J. J. van Zyl. VegetationCharacteristics and Surface Topography from Interferometric Radar.Radio Science, 1996, 31:14491485
[38] R. N. Treuhaft, S. R. Cloude. The Structure of Oriented Vegetation from Polarimetric Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(5):2620-2624
[39] R. N. Treuhaft. Vertical Structure of Vegetated Land Surfaces from Interferometric and Polarimetric Radar. Radio Sciences, 2000, 35(1):141-177
[40] H. Yamada, Y. Yamaguchi, E. Rodriguez, Y. Kim, W. M.Boerner. Polarimetric SAR Interferometry for Forest Canopy Analysis by Using the Super-resolution Method. IEICE Transactions on Electronics, December 2001, 84(12):1917-1924
[41] E. Colin, C. Titin-Schneider, W. Tabbara. Investigation of Different Interferometric Coherence Optimisation Methods. Proceedings of ESA Workshop on Applications of SAR Polarimetry and Polarimetric Interferometry(POLInSAR 03) , January 2003
[42] S. R. Cloude, K. P. Papathanssiou, A. Reigber. Polarimetric SAR Interferometry at P Band for Vegetation Structure Extraction. Proceedings of European SAR Conference EUSAR 2000, Munich, Germany, May 2000:249-252
[43] K. P. Papathanassiou, S. R. Cloude, A. Reigber. Single and Multi-Baseline Polarimetric SAR Interferometry over Forested Terrain. Proceedings of European SAR Conference EUSAR 2000, Munich, Germany, May 2000:123-126
[44]张腊梅.L波段PoIInSAR图像地表参数反演方法研究:[硕士学位论文].2006,哈尔滨工业大学
[45] S. R. Cloude, K. P. Papathanassiou. A 3-Stage Inversion Process for Polarimetric SAR Interferometry. Proc of EUSAR2002, Cologne, Germany, June 2002:297-282
[46] S R. Cloude, K. P. Papathanassiou. Three-stage Inversion Process for Polarimetric SAR Interferometry. IEE Proc Radar Sonar Navig, 2003, 150(3):125-134
[47] M. Tabb, R. Carande. Robust Inversion of Vegetation Structure Parameters from Low Frequency Polarimetric Interferometric SAR. Proceedings of IEEE International Geoscience and Remote Sensing Symposium(IGARSS 2001), Sydney, Australia, July 2001
[48] M. Tabb, T. Flynn, R. Carande. Direct Estimation of Vegetation Parameters from Covariance Data in POLINSAR. Proceedings of IGARSS 2002, Toronto, Canada, 2002
[49] S. R. Cloude. Robust Parameter Estimation Using DualBaseline Polarimetric SAR Interferometry, Processing of International Geoscience and Remote Sensing Symposium 2002, 2002
[50] S. R. Cloude, M. L. Williams. A Coherent EM Scattering Model for Dual Baseline POLInSAR, Processing of International Geoscience and Remote Sensing Symposium 2003, 2003
[51] S. R. Cloude. Dual-Baseline Coherence Tomography. IEEE Transactions on Geoscience and Remote Sensing, 2007, 4(1):127-131
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