极化SAR信息处理技术研究
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摘要
极化合成孔径雷达(POLSAR)比单极化合成孔径雷达(SAR)包含了更丰富的目标信息,已经成为国内外微波成像发展的热门方向之一。电磁波的极化对目标介电常数、物理特性、几何尺寸和取向等比较敏感,通过不同的收发天线组合测量可以得到反映目标散射特性的极化散射矩阵,这为图像理解和目标分析奠定了基础。
目标特征量的提取是极化信息处理的基础,特征量提取的过程不仅是物理问题,也是数学问题,所提取的特征量不仅要反映目标的散射特性,还要有合适的数学实现。论文在较系统的研究目标特征量提取方法和特征量所包含的物理意义的基础上,对极化SAR图像降斑、极化对比增强、极化SAR图像分类以及极化SAR图像中海上舰船目标检测等方面进行了研究,并提出了一些新的概念和方法,对实测数据的处理结果表明,这些新的概念和方法对于极化SAR信息处理是有效的,本文的主要创新成果包括以下方面:
1)针对基于预分类的MMSE极化降斑方法实现过程非常复杂的问题,提出了简化方案,并验证了方案的有效性;
2)扩展了极化相关系数的表示方法,这种扩展增强了极化相关系数对目标的区分效果;另外还提出了极化特征图量化参数,可以从量上表征不同目标间相同极化和交叉极化的回波功率差异和极化特征图形状差异;
3)定义了目标间的差异度参数,它不仅可以用于描述相干目标,还可以用于描述分布目标的差别程度。并将目标差异参数度应用于极化分类,构造了基于差异度的迭代分类方法,这种方法比传统的Wishart分类具有更好的边缘保持效果,并具有更强的鲁棒性和更易于编程实现的特点;
4)针对海上舰船的对比增强,提出了自动划分舰船样本的方法,这种划分比人工划分具有更强的鲁棒性,并研究了舰船与海面、舰船与岛屿和舰船与海上其他人造目标的对比增强,针对相近散射机理目标的对比增强程度非常有限的问题,验证了基于不同极化通道间的代数运算来提高舰船和杂波对比度是可行的,为目标的对比增强研究提供了新的思路;
5)将极化分类方法应用于海上舰船检测,验证了这种方法的可行性,并提出了基于特征矢量分类的舰船检测方法,得到了很好的舰船与海面、舰船与岛屿以及舰船与海上其他人造目标的分离效果,并保存了舰船尾迹等有用信息,另外还提出了针对舰船检测的目标鉴别方法,这种方法基于同极化相位差判断回波最强类是否对应舰船目标,这种鉴别方法简便易行并且是非常有效的。
Compared with the single polarized SAR (synthetic aperture radar), polarimetric SAR (Pol-SAR) holds more information of targets, which is one of the most important aspects of the microwave imaging research and development. Polarimetry properties of electromagnetic (EM) waves are sensitive to the scatters permittivity, physical trait, size, orientation and so on. The polarimetric scattering matrix, which describes the backscattering properties of targets completely, can be measured by transmitting and receiving different polarized signals.
The Pol-SAR processing is based on information extraction of targets, which involves both physics and mathematics, i.e. not only reflects its scattering properties, but achieves it in mathematics. In this dissertation, based on the extraction of meaningful polarization information, the polarimetric speckle reduction, polarimetric contrast enhancement, polarimetric classification and ship detection in polarimetric SAR images are systemically studied. During the study, some new concepts and methods are introduced, which are supported by the application to measured Pol-SAR data. The innovations of this dissertation are as follows:
1) A simplified schem is proposed to reduce the complexity of scattering-model-based speckle filtering.
2) Extend the expression of polarimetric correlation coefficient to help distinguishing targets. In addition, introduce the quantized parameters of polarimetric signature so as to show the differentiae in quantity in co-polar power, cross-polar power and shapes of polarization signatures among targets.
3) Define a new parameter of difference degree between targets, which can be used for express the difference between both coherent and distributed scatters. Besides, the difference degree is applied to polarimetric classification. A new unsupervised iterative classification method based on difference degree is proposed, which is better in keeping edges, more robust and simpler to programming than Wishart classifier.
4) Develop a new method to sample ships adaptively, which is used for polarimetric contrast enhancement. The adaptive method is more robust than choosing ships samples manually. Our research shows that the enhanced degree is not very notable between the similar scattering targets using polarimetric contrast enhancement. We also verify the way is feasible to enhance the contrast between ships and clutter by algebraic operation to different polarimetric channels.
5) Use the polarimetric classification into ship detection. We propose a new ship detection method base on feature vector, which can detect ships form the sea, island and other man-made objects. At the same time, we propose the method of ship discrimination based on the co-pol phase difference. The application to AIRSAR and SIR-C data shows it is simple and effective.
目标特征量的提取是极化信息处理的基础,特征量提取的过程不仅是物理问题,也是数学问题,所提取的特征量不仅要反映目标的散射特性,还要有合适的数学实现。论文在较系统的研究目标特征量提取方法和特征量所包含的物理意义的基础上,对极化SAR图像降斑、极化对比增强、极化SAR图像分类以及极化SAR图像中海上舰船目标检测等方面进行了研究,并提出了一些新的概念和方法,对实测数据的处理结果表明,这些新的概念和方法对于极化SAR信息处理是有效的,本文的主要创新成果包括以下方面:
1)针对基于预分类的MMSE极化降斑方法实现过程非常复杂的问题,提出了简化方案,并验证了方案的有效性;
2)扩展了极化相关系数的表示方法,这种扩展增强了极化相关系数对目标的区分效果;另外还提出了极化特征图量化参数,可以从量上表征不同目标间相同极化和交叉极化的回波功率差异和极化特征图形状差异;
3)定义了目标间的差异度参数,它不仅可以用于描述相干目标,还可以用于描述分布目标的差别程度。并将目标差异参数度应用于极化分类,构造了基于差异度的迭代分类方法,这种方法比传统的Wishart分类具有更好的边缘保持效果,并具有更强的鲁棒性和更易于编程实现的特点;
4)针对海上舰船的对比增强,提出了自动划分舰船样本的方法,这种划分比人工划分具有更强的鲁棒性,并研究了舰船与海面、舰船与岛屿和舰船与海上其他人造目标的对比增强,针对相近散射机理目标的对比增强程度非常有限的问题,验证了基于不同极化通道间的代数运算来提高舰船和杂波对比度是可行的,为目标的对比增强研究提供了新的思路;
5)将极化分类方法应用于海上舰船检测,验证了这种方法的可行性,并提出了基于特征矢量分类的舰船检测方法,得到了很好的舰船与海面、舰船与岛屿以及舰船与海上其他人造目标的分离效果,并保存了舰船尾迹等有用信息,另外还提出了针对舰船检测的目标鉴别方法,这种方法基于同极化相位差判断回波最强类是否对应舰船目标,这种鉴别方法简便易行并且是非常有效的。
Compared with the single polarized SAR (synthetic aperture radar), polarimetric SAR (Pol-SAR) holds more information of targets, which is one of the most important aspects of the microwave imaging research and development. Polarimetry properties of electromagnetic (EM) waves are sensitive to the scatters permittivity, physical trait, size, orientation and so on. The polarimetric scattering matrix, which describes the backscattering properties of targets completely, can be measured by transmitting and receiving different polarized signals.
The Pol-SAR processing is based on information extraction of targets, which involves both physics and mathematics, i.e. not only reflects its scattering properties, but achieves it in mathematics. In this dissertation, based on the extraction of meaningful polarization information, the polarimetric speckle reduction, polarimetric contrast enhancement, polarimetric classification and ship detection in polarimetric SAR images are systemically studied. During the study, some new concepts and methods are introduced, which are supported by the application to measured Pol-SAR data. The innovations of this dissertation are as follows:
1) A simplified schem is proposed to reduce the complexity of scattering-model-based speckle filtering.
2) Extend the expression of polarimetric correlation coefficient to help distinguishing targets. In addition, introduce the quantized parameters of polarimetric signature so as to show the differentiae in quantity in co-polar power, cross-polar power and shapes of polarization signatures among targets.
3) Define a new parameter of difference degree between targets, which can be used for express the difference between both coherent and distributed scatters. Besides, the difference degree is applied to polarimetric classification. A new unsupervised iterative classification method based on difference degree is proposed, which is better in keeping edges, more robust and simpler to programming than Wishart classifier.
4) Develop a new method to sample ships adaptively, which is used for polarimetric contrast enhancement. The adaptive method is more robust than choosing ships samples manually. Our research shows that the enhanced degree is not very notable between the similar scattering targets using polarimetric contrast enhancement. We also verify the way is feasible to enhance the contrast between ships and clutter by algebraic operation to different polarimetric channels.
5) Use the polarimetric classification into ship detection. We propose a new ship detection method base on feature vector, which can detect ships form the sea, island and other man-made objects. At the same time, we propose the method of ship discrimination based on the co-pol phase difference. The application to AIRSAR and SIR-C data shows it is simple and effective.
引文
[1] 张澄波.综合孔径雷达原理、系统分析与应用[M].北京:科学出版社,1989
[2] 杨士中. 合成孔径雷达[M]. 北京:科学出版社,1981
[3] 庄钊文,肖顺平,王雪松.雷达极化信息处理及其应用[M].北京:国防工业出版社,1999
[4] Harold Mott.天线和雷达中的极化[M].林昌禄,译.成都:电子科技大学出版社,1989
[5] Wiley, C. A.. Synthetic Aperture Radars-A Paradigm for Technology Evolution, IEEE Trans. on AES,1985,21(3):440-443
[6] 戴博伟.多极化合成孔径雷达系统与极化信息处理研究[D].北京:中科院电子所,2000
[7] VanZyl J. J.. AIRSAR Reference Manual[EB]. HTTP://airsar.jpl.nasa.gov/documents/instrument.htm, Jet Propulsion Laboratory
[8] 王被德.近三年来雷达极化研究的进展[J].现代雷达,1996,18(1):1-14
[9] Pottier E., Ferro-Famil L.. Polarimetric Airborne SAR Sensors[EB]. http://earth.esa.int/polsarpro/datasets.html, 2004
[10]吴曼青.多波段、多极化机载 SAR 系统及飞行试验[C].2005 年中国合成孔径雷达会议交流论文.南京:2005
[11]Henri Maitre.合成孔径雷达图像处理[M].孙洪,译.北京:电子工业出版社,2005
[12] Sinclair G.. The Transmission and Reception of Elliptical Polarized Wave. Proc. IRE, 1950, 38(2): 148-151
[13] Kennaugh E. M.. Polarization Properties of Radar Reflections[D]. Columbus: The Ohio State University, 1952
[14] Graves C. D.. Radar Polarization Power Scattering Matrix[J]. Proc. IRE, 1956, 44(5) 248-252
[15] Huynen J. R.. Phenomenological Theory of Radar Targets[D], Ph. D. Dissertation. 1970
[16] Pottier E.. On Dr. J. R. Huynen's main contributions in the development of polarimetric radar techniques and how the 'Radar Targets Phenomenological Concept' becomes a theory [J]. Proceedings of SPIE , 1992, 1748:72-85
[17] Boerner W. M., Yan W.L, Xi A.Q.,et al. On the Basic Principles of Radar Polarimetry: the Target Characteristic Polarization State Theory of Kennaugh, Huynen’s Polarization Fork Concept, and Its Extension to the Partially Polarized Case. Proceedings of the IEEE, 1991, 79(10): 1538-1550
[18] Swartz A. A., Yueh H. A., Kong J. A.. Optimal polarizations for achieving maximum contrast in radar images [J]. Journal of geophysical research, 1988, 93(12B):15252-15260
[19]杨健.杂波情况下雷达天线的最优极化[J].西北工业大学学报,1994,12(2):316-320
[20] Jian Y., Yamaguchi Y., Boerner W. M. , et al. Numerical methods for solving the optimal problem of contrast enhancement [J]. IEEE Trans.Geosci.Remote Sensing, 2000, 38(2):965-971
[21] Joughin I. R., Winebrenner D. P., Percival D. B.. Probability density functions for multilook polarimetric signatures [J]. IEEE Trans.on Geoscience and Remote Sensing, 1994, 32(3):562-574
[22] Lee J. S., Hoppel K. W., Mango S. A. , et al. Intensity and phase statistics of multilook polarimetric and interferometric SAR imagery [J]. IEEE Trans.on Geoscience and Remote Sensing, 1994, 32(5):1017-1028
[23] Lee J. S., Schuler D. L., Lang R. H. , et al. K-distribution for multi-look processed polarimetric SAR imagery[C]. Presented at IGARSS'94. Pasadena, California: 1994
[24] 陆岩.多视极化合成孔径雷达 K 分布研究[D].成都:电子科技大学,2000
[25] Cameron W L, Leung L K. Feature Motived Polarization scattering matrix decomposion[C]. Presented at IEEE International Radar Conference. 1990
[26] Touzi R., Charbonneau F..Characterization of target symmetric scattering using polarimetric SARs[J].IEEE Trans.on Geoscience and Remote Sensing,2002,40(11):2507-2516
[27] Touzi R. On the use of polarimetric SAR data for ship detection[C]. Presented at IGARSS '99. Hamburg, Germany: 1999
[28] Touzi R., Charbonneau F.. The SSCM for ship characterization using polarimetric SAR[C]. Presented atIGARSS '03. Toulouse: 2003
[29] Touzi R, Raney R K, Charbonneau F. On the use of permanent symmetric scatterers for ship characterization[C]. Presented at IGARSS'04. Alaska: 2004
[30] Krogager E. New decomposition of the radar target scattering matrix [J]. Electronics Letters, 1990, 26(18):1525-1527
[31] Freeman A., Durden S. L.. A three-component scattering model for polarimetric SAR data [J]. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(3):963-973
[32] Lee J. S., Grunes M. R., Schuler D. L. , et al. Scattering-Model-Based Speckle Filtering of Polarimetric SAR Data [J]. IEEE Trans.on Geoscience and Remote Sensing, 2006, 44(1):176-187
[33] Lee J. S., Grunes M. R., Pottier E. , et al. Unsupervised terrain classification preserving polarimetric scattering characteristics [J]. IEEE Trans.on Geoscience and Remote Sensing, 2004, 42(4):722-731
[34] Yamaguchi Y., Moriyama T.. Four-component scattering model for polarimetric SAR image decomposition [J]. IEEE Trans. Geosci. Remote Sensing, 2005, 43(8):1699-1706
[35] Yamaguchi Y., Yajima Y., Yamada H.. Four-component decomposition of POLSAR image based on coherency matrix[C]. Presented at EUSAR2006. Dresden: 2006
[36] Yamaguchi Y., Yajima Y., Yamada H.. A Four-Component Decomposition of POLSAR Images Based on the Coherency Matrix [J]. IEEE Geoscience and Remote Sensing Letters, 2006, 3(3):292-296
[37] Moriyama T., Uratsuka S., Umehara T. , et al. Feature extraction of urban area based on polarimetric decomposition[C]. EUSAR’04. 2004
[38] Cloude S.R..Target decomposition theorms in radar scattering[J].Electronic letters,1985,21(1): 22-24
[39] Cloude S. R., Pottier E.. A review of target decomposition theorems in radar polarimetry[J]. IEEE Trans. Geosci. Remote Sensing, 1996, 34(2): 498-518
[40] Cloude S. R., Eric Pottier, An entropy based classification scheme for land applications of polarimetric SAR[J]. IEEE Trans.Geosci.Remote Sensing, 1997, 35(1): 68-78
[41] Cloude S. R., Pottier E.. Application of the H/A/alpha polarimetric decomposition theorem for land classification [J]. Proceedind of SPIE , 1997, 3120:132-143
[42] Yang J, Peng Y, Lin S. Similarity between two scattering matrices [J]. Electronics Letters, 2001, 37(3):193-194
[43] 高明星.基于极化 SAR 的目标特征提取及其应用[D].北京:清华大学,2004
[44] 范立生,高明星,杨 健,等.极化 SAR 遥感中森林特征的提取[J].电波科学学报,2005,20(5):553-556
[45] Van Zyl J.. Unsupervised classification of scattering behavior using radar polarimetry data [J]. IEEE Trans. Geosci. Remote Sensing, 1989, 27(1):36-45
[46] Kong J. A., Swartz A. A.. Identification of Terrain Cover Using the Optimal Terrain Classifier, J., Electronmagn. Waves Applicat., 1988, 2: 171-194
[47] Lee J. S., Grunes M. R., Kwok R.. Classification of Multi-look Polarimetric SAR Imagery Based on Complex Wishart Distribution [J]. Int. J. Remote Sensing, 1994, 15(11):2299-2311
[48] Lee J.S., Grunes M.R., Ainsworth T.L., et al.. Unsupervised classification using polarimetric decomposition and the complex Wishart classifier[J]. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(5):2249-2258
[49] Pottier E., Lee J. S.. Unsupervised classification scheme of polsar images based on the complex wishart distribution and the H/A/a polarimetric decomposition theorem[C]. Presented at EUSAR2000. Munich: 2000
[50] Du L., Lee J. S.. Fuzzy Classification of Earth Terrain Covers Using Complex Polarimetric SAR Data. Int. J. Remote Sensing, 1996, 17(4): 809-826
[51] Martin H., Gunther J.. Fuzzy rule based classification of polarimetric SAR data [J]. Aerospace Science and Technology, 2002, 6(3):217-232
[52] Kersten P.R., Lee J.S., Ainsworth T.L.. Unsupervised classification of polarimetric synthetic aperture radar images using fuzzy clustering and EM clustering[J]. IEEE Trans.Geosci.Remote Sensing, 2005, 43(3):519-527
[53] Van Zyl J. J., Burnette C F. Bayesian Classification of Polarimetric SAR images using adaptive a priori probabilities. Int. J. Remote Sensing, 1992, 13(5): 835-840
[54] Ferro-Famil L., Pottier E., Lee J. S.. Unsupervised classification of multi-frequency and fully polarimetric SAR images based on the H A Alpha Wishart classifier[C]. Presented at IGARSS 2000. Hawaii: 2000
[55] Lemoine G. G., Grandi G. F. D., Sieber A. J.. Polarimetric Contrast Classification of Agricultural Fields Using MAESTRO1 AIRSAR Data. Int. J. Remote Sensing, 1994, 15(14): 2851-2869
[56] Schuler D. L., Lee J. S. , Grandi G. De, The Remote Sensing of Topography Using Polarimetric SAR, Presented at IGARSS’95, 1995
[57] Hajnsek I, Cloude S R, Lee J S , et al. Inversion of surface parameters from polarimetric SAR data[C]. Presented at IGARSS 2000. Honolulu, Hawaii: 2000
[58] Hajnsek I., Pottier E., Cloude S. R.. Inversion of surface parameters from polarimetric SAR [J]. IEEE Trans.on Geoscience and Remote Sensing, 2003, 41(4):727-744
[59] Lee H., Chen K., Lee J., et al. A comparisons of model based and image based surface parametersestimation from polarimetric SAR[C]. Presented at IGARSS 2005. Seoul: 2005
[60] 王翠珍.极化 SAR 数据分析与目标信息提取[D].北京:中科院遥感所,1999
[61] 刘秀清.全极化合成孔径雷达极化信息处理技术研究[D].北京:中科院电子所,2004
[62] 徐俊毅.极化雷达遥感图像分类研究[D].北京:清华大学电子工程系,2002
[63] Novak L. M., Burl M. C.. Optimal speckle reduction in polarimetric SAR imagery [J]. IEEE Transactions on Aerospace and Electronic Systems, 1990, 26(2):293-305
[64] Lee J. S., Grunes M. R., Mango S. A.. Speckle reduction in multipolarization,multifrequency SAR imagery [J]. IEEE Trans. Remote Sensing, 1991, 29(4):535-544
[65] Lopes A., Goze S., Nezry E.. Polarimetric Speckle Filters For SAR Data[C]. Presented at IGARSS'92. Houston: 1992
[66] Lee J. S., Grunes M. R., Grandi. Polarimetric SAR speckle filtering and its implication for classification [J]. IEEE Trans.Geosci.Remote Sensing, 1999, 37(5):2363-2373
[67] Novak L. M., Burl M. C., Irving W.W., et al. Optimal polarimetric processing for enhanced target detection[C]. Presented at Telesystems Conference. NTC '91, 1991
[68] Novak L. M., Burl M. C., Irving W. W.. Optimal polarimetric processing for enhanced target detection [J]. IEEE Transaction on Areospace and Electronic Systems, 1993, 29(1):234-244
[69] Novak L. M.,Halversen S. D., Owirka G. J., et al. Effects of polarization and resolution on SAR ATR [J]. IEEE Transactions on Aerospace and Electronic Systems,1997, 33(1):102—116
[70] Andrew P., Robert R., Kotska O., et al. Land target detection using high resolution mufti-polarimetric SAR data [C]. IGARSS’98, Seattle, USA, 1998
[71] Lee J. S..Digital Image Enhancement and Noise Filtering by Use of Local Statistics[J].IEEE Tans.Pattern Analysis and Machine Intelligence,1980,PAMI-2(2):165-168
[72] Lee J. S., Grunes M. R., Grandi G. De. Polarimetric SAR speckle filtering and its impact on classification[C]. Presented at IGASS'97. Singapore: 1997
[73] Touzi R., Lopes A.. The principle of speckle filtering in polarimetric SAR imagery [J]. IEEE Trans. Geosci. Romote Sensing, 1994, 32(5):1110-1114
[74] 刘秀清,杨震,杨汝良.全极化合成孔径雷达图像极化白化滤波参数估计方法的改进研究[J].电子学报,2003,31(12):1795-1799
[75] Sang-Ho Yoon, Young-Soo Kim. Classified pixel-based windowing algorithm for polarimetric SAR speckle filtering[J]. Electronics Letters,2003,39(1):115-117
[76] 舒宁.微波遥感原理[M].1.武汉:武汉测绘大学出版社,2000
[77] Lopez-Martinez C., Ferro-Famil L., Pottier E.. Polarimetry Tutorial[EB]. http://eartch.esa.int:80/polsarpro/tutorial.html,2005
[78] Touzi R., Charbonneau F., Hawkins R. K. , et al. Ship-sea contrast optimization when using polarimetric SARs[C]. Presented at IGARSS '01. Sydney: 2001
[79] Dubois P. C., van Zyl J., Engman T.. Measuring soil moisture with imaging radars [J]. IEEE Trans. Geiosci. Remote Sensing, 1995, 33(4):915-926
[80] Borgeaud M., Nell J.. Comparisons Of Theoretical Surface Scattering Models For Polarimetric Microwave Remote Sensing[C]. Presented at IGARSS'92. 1992
[81] Borgeaud M., Noll J.. Analysis of theoretical surface scattering models for polarimetric microwave remote sensing of bare soils. International Journal of Remote Sensing,1994,15(14): 2931-2942
[82] Kozlov A. I., Ligthart L. P., Logvin A. I.. Mathematical and Physical Modelling of Microwave Scattering and Polarimetric Remote Sensing[M]. Boston: Kluwer Academic Publishers, 2001
[83]姚鲁.全极化 SAR 水面船只目标探测的研究[R].国家海洋局第二海洋研究所,2006
[84] Touzi R., Boerner W. M., Lee J. S. , et al. A review of polarimetry in the context of synthetic aperture radar: concepts and information extraction [J]. Can. J. Remote Sensing, 2004, 30(3):380-407
[85] Youan K.. Invariant characters on radar cross section of polarized radar targets[C]. IEEE International Conference on Radar, 2000
[86]郭德方.遥感图像的计算机处理和模式识别[M].北京:电子工业出版社,1987
[87]徐俊毅,杨健,彭应宁.极化雷达目标检测中的鉴别信息[C].第八界全国雷达学术年会交流论文.合肥:2002
[88]徐俊毅, 杨健, 彭应宁.相似性参数在极化雷达遥感图像分析中的作用[C].第八届全国雷达年会交流论文.合肥:2002
[89] 陈祖明,周家胜.矩阵论引论[M].北京:北京航空航天大学出版社,2000
[90] Wang wenguang, Wang Jun., Mao Shiyi. Classification of polarimetric SAR images based on difference degree[C]. Presented at EUSAR2006. Dresden: 2006
[91]王文光,王俊,毛士艺.一种基于差异度的极化 SAR 迭代分类方法[J].电子与信息学报,2006,28(11):2007-2010
[92] Inannidis G. A., Hamers D. E.. Optimum antenna polarizations for target discrimaination in clutter. IEEE trans. antennas propag., 1979, ap-27:357-363
[93] Kostinski A., Boerner W..on the Polarimetric Contrast Optimization[J]. IEEE Trans.on A.P., 1987, AP-35(8): 988-991
[94] 杨健,董贵威,彭应宁.广义相对最优极化及其应用[C].中国航空学会电子专业委员会 2003学术交流会交流论文.上海:2003
[95] Jian Y., Guiwei D., Yingning P. , et al. Generalized optimization of polarimetric contrast enhancement [J]. IEEE Geoscience and Remote Sensing Letters, 2004, 1(3):171-174
[96] Yang J., Yamaguchi Y., Yamada H..Co-null of targets and co-null Abelian group[J]. Electronics Letters, 1999, 35(12): 1017-1019
[97] Yang J., Yamaguchi Y., Yamada H. , et al. Development of target null theory [J]. IEEE Trans.Geosci.Remote Sensing, 2001, 39(2):330-338
[98] Cao Fang, Hong Wen, Wu Yirong. An improved cloude-pottier decomposition using H/α/span and complex wishart classifier for polarimetric SAR classification[C]. Presented at 2006 CIE international conference on radar. Shanghai: 2006
[99] 刘秀清,杨汝良.基于全极化 SAR 非监督分类的迭代分类方法[J].电子学报,2004,32(12):1982-1986
[100] Zhang Haijian,Yang Wen, Chen Jiayu , et al..Improved classification of polarimetric SAR data based on four-component scattering model[C]. Presented at 2006 CIE international conference on radar. Shanghai: 2006
[101] Yeremy M., Campbell J. W., Mattar K. , et al. Ocean surveillance with polarimetric SAR [J]. Can.J.Remote Sensing, 2001, 27(4):328-344
[102] 张宇,张永刚,黄韦艮.星载 SAR 船舶及尾迹探测技术研究[J].遥感技术与应用,2003,18(1):31-35
[103] 张宇,张永刚,黄韦艮,等.一种利用 SAR 图像检测船舶尾迹的方法[J].国土资源遥感,2003,(1):56-58
[104] Pottier E., Boerner W. M., Schuler D. L.. Polarimetric detection and estimation of ship wakes[C]. Presented at IGARSS'99. 1999
[105] 钟雪莲.SAR 图像中人造目标的检测和辨别[D].北京:中科院遥感应用研究所,2005
[106] Rey M.T., Tunaley J.K., Folinsbee J.T., et al.. Application of radon transform techniques to wake detection in Seasat-A SAR Images[J]. IEEE Trans.Geosci.Remote Sensing, 1990, 28(4): 553-560
[107] Copeland A.C., Ravichandran G., Trivedi M.M.. Localized Radon transform-based detection of ship wakes in SAR images[J]. IEEE Trans.Geosci.Remote Sensing, 1995, 33(1): 35-45
[108] Imbo P., Souyris J., Yeremy M.. Wake detection in polarimetric SAR images[C]. Presented at IGARSS'01. 2001
[109] Courmontagne P.. An improvement of ship wake detection based on the radon transform[J]. Signal Processing, 2005 , 85(8): 1634-1654
[2] 杨士中. 合成孔径雷达[M]. 北京:科学出版社,1981
[3] 庄钊文,肖顺平,王雪松.雷达极化信息处理及其应用[M].北京:国防工业出版社,1999
[4] Harold Mott.天线和雷达中的极化[M].林昌禄,译.成都:电子科技大学出版社,1989
[5] Wiley, C. A.. Synthetic Aperture Radars-A Paradigm for Technology Evolution, IEEE Trans. on AES,1985,21(3):440-443
[6] 戴博伟.多极化合成孔径雷达系统与极化信息处理研究[D].北京:中科院电子所,2000
[7] VanZyl J. J.. AIRSAR Reference Manual[EB]. HTTP://airsar.jpl.nasa.gov/documents/instrument.htm, Jet Propulsion Laboratory
[8] 王被德.近三年来雷达极化研究的进展[J].现代雷达,1996,18(1):1-14
[9] Pottier E., Ferro-Famil L.. Polarimetric Airborne SAR Sensors[EB]. http://earth.esa.int/polsarpro/datasets.html, 2004
[10]吴曼青.多波段、多极化机载 SAR 系统及飞行试验[C].2005 年中国合成孔径雷达会议交流论文.南京:2005
[11]Henri Maitre.合成孔径雷达图像处理[M].孙洪,译.北京:电子工业出版社,2005
[12] Sinclair G.. The Transmission and Reception of Elliptical Polarized Wave. Proc. IRE, 1950, 38(2): 148-151
[13] Kennaugh E. M.. Polarization Properties of Radar Reflections[D]. Columbus: The Ohio State University, 1952
[14] Graves C. D.. Radar Polarization Power Scattering Matrix[J]. Proc. IRE, 1956, 44(5) 248-252
[15] Huynen J. R.. Phenomenological Theory of Radar Targets[D], Ph. D. Dissertation. 1970
[16] Pottier E.. On Dr. J. R. Huynen's main contributions in the development of polarimetric radar techniques and how the 'Radar Targets Phenomenological Concept' becomes a theory [J]. Proceedings of SPIE , 1992, 1748:72-85
[17] Boerner W. M., Yan W.L, Xi A.Q.,et al. On the Basic Principles of Radar Polarimetry: the Target Characteristic Polarization State Theory of Kennaugh, Huynen’s Polarization Fork Concept, and Its Extension to the Partially Polarized Case. Proceedings of the IEEE, 1991, 79(10): 1538-1550
[18] Swartz A. A., Yueh H. A., Kong J. A.. Optimal polarizations for achieving maximum contrast in radar images [J]. Journal of geophysical research, 1988, 93(12B):15252-15260
[19]杨健.杂波情况下雷达天线的最优极化[J].西北工业大学学报,1994,12(2):316-320
[20] Jian Y., Yamaguchi Y., Boerner W. M. , et al. Numerical methods for solving the optimal problem of contrast enhancement [J]. IEEE Trans.Geosci.Remote Sensing, 2000, 38(2):965-971
[21] Joughin I. R., Winebrenner D. P., Percival D. B.. Probability density functions for multilook polarimetric signatures [J]. IEEE Trans.on Geoscience and Remote Sensing, 1994, 32(3):562-574
[22] Lee J. S., Hoppel K. W., Mango S. A. , et al. Intensity and phase statistics of multilook polarimetric and interferometric SAR imagery [J]. IEEE Trans.on Geoscience and Remote Sensing, 1994, 32(5):1017-1028
[23] Lee J. S., Schuler D. L., Lang R. H. , et al. K-distribution for multi-look processed polarimetric SAR imagery[C]. Presented at IGARSS'94. Pasadena, California: 1994
[24] 陆岩.多视极化合成孔径雷达 K 分布研究[D].成都:电子科技大学,2000
[25] Cameron W L, Leung L K. Feature Motived Polarization scattering matrix decomposion[C]. Presented at IEEE International Radar Conference. 1990
[26] Touzi R., Charbonneau F..Characterization of target symmetric scattering using polarimetric SARs[J].IEEE Trans.on Geoscience and Remote Sensing,2002,40(11):2507-2516
[27] Touzi R. On the use of polarimetric SAR data for ship detection[C]. Presented at IGARSS '99. Hamburg, Germany: 1999
[28] Touzi R., Charbonneau F.. The SSCM for ship characterization using polarimetric SAR[C]. Presented atIGARSS '03. Toulouse: 2003
[29] Touzi R, Raney R K, Charbonneau F. On the use of permanent symmetric scatterers for ship characterization[C]. Presented at IGARSS'04. Alaska: 2004
[30] Krogager E. New decomposition of the radar target scattering matrix [J]. Electronics Letters, 1990, 26(18):1525-1527
[31] Freeman A., Durden S. L.. A three-component scattering model for polarimetric SAR data [J]. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(3):963-973
[32] Lee J. S., Grunes M. R., Schuler D. L. , et al. Scattering-Model-Based Speckle Filtering of Polarimetric SAR Data [J]. IEEE Trans.on Geoscience and Remote Sensing, 2006, 44(1):176-187
[33] Lee J. S., Grunes M. R., Pottier E. , et al. Unsupervised terrain classification preserving polarimetric scattering characteristics [J]. IEEE Trans.on Geoscience and Remote Sensing, 2004, 42(4):722-731
[34] Yamaguchi Y., Moriyama T.. Four-component scattering model for polarimetric SAR image decomposition [J]. IEEE Trans. Geosci. Remote Sensing, 2005, 43(8):1699-1706
[35] Yamaguchi Y., Yajima Y., Yamada H.. Four-component decomposition of POLSAR image based on coherency matrix[C]. Presented at EUSAR2006. Dresden: 2006
[36] Yamaguchi Y., Yajima Y., Yamada H.. A Four-Component Decomposition of POLSAR Images Based on the Coherency Matrix [J]. IEEE Geoscience and Remote Sensing Letters, 2006, 3(3):292-296
[37] Moriyama T., Uratsuka S., Umehara T. , et al. Feature extraction of urban area based on polarimetric decomposition[C]. EUSAR’04. 2004
[38] Cloude S.R..Target decomposition theorms in radar scattering[J].Electronic letters,1985,21(1): 22-24
[39] Cloude S. R., Pottier E.. A review of target decomposition theorems in radar polarimetry[J]. IEEE Trans. Geosci. Remote Sensing, 1996, 34(2): 498-518
[40] Cloude S. R., Eric Pottier, An entropy based classification scheme for land applications of polarimetric SAR[J]. IEEE Trans.Geosci.Remote Sensing, 1997, 35(1): 68-78
[41] Cloude S. R., Pottier E.. Application of the H/A/alpha polarimetric decomposition theorem for land classification [J]. Proceedind of SPIE , 1997, 3120:132-143
[42] Yang J, Peng Y, Lin S. Similarity between two scattering matrices [J]. Electronics Letters, 2001, 37(3):193-194
[43] 高明星.基于极化 SAR 的目标特征提取及其应用[D].北京:清华大学,2004
[44] 范立生,高明星,杨 健,等.极化 SAR 遥感中森林特征的提取[J].电波科学学报,2005,20(5):553-556
[45] Van Zyl J.. Unsupervised classification of scattering behavior using radar polarimetry data [J]. IEEE Trans. Geosci. Remote Sensing, 1989, 27(1):36-45
[46] Kong J. A., Swartz A. A.. Identification of Terrain Cover Using the Optimal Terrain Classifier, J., Electronmagn. Waves Applicat., 1988, 2: 171-194
[47] Lee J. S., Grunes M. R., Kwok R.. Classification of Multi-look Polarimetric SAR Imagery Based on Complex Wishart Distribution [J]. Int. J. Remote Sensing, 1994, 15(11):2299-2311
[48] Lee J.S., Grunes M.R., Ainsworth T.L., et al.. Unsupervised classification using polarimetric decomposition and the complex Wishart classifier[J]. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(5):2249-2258
[49] Pottier E., Lee J. S.. Unsupervised classification scheme of polsar images based on the complex wishart distribution and the H/A/a polarimetric decomposition theorem[C]. Presented at EUSAR2000. Munich: 2000
[50] Du L., Lee J. S.. Fuzzy Classification of Earth Terrain Covers Using Complex Polarimetric SAR Data. Int. J. Remote Sensing, 1996, 17(4): 809-826
[51] Martin H., Gunther J.. Fuzzy rule based classification of polarimetric SAR data [J]. Aerospace Science and Technology, 2002, 6(3):217-232
[52] Kersten P.R., Lee J.S., Ainsworth T.L.. Unsupervised classification of polarimetric synthetic aperture radar images using fuzzy clustering and EM clustering[J]. IEEE Trans.Geosci.Remote Sensing, 2005, 43(3):519-527
[53] Van Zyl J. J., Burnette C F. Bayesian Classification of Polarimetric SAR images using adaptive a priori probabilities. Int. J. Remote Sensing, 1992, 13(5): 835-840
[54] Ferro-Famil L., Pottier E., Lee J. S.. Unsupervised classification of multi-frequency and fully polarimetric SAR images based on the H A Alpha Wishart classifier[C]. Presented at IGARSS 2000. Hawaii: 2000
[55] Lemoine G. G., Grandi G. F. D., Sieber A. J.. Polarimetric Contrast Classification of Agricultural Fields Using MAESTRO1 AIRSAR Data. Int. J. Remote Sensing, 1994, 15(14): 2851-2869
[56] Schuler D. L., Lee J. S. , Grandi G. De, The Remote Sensing of Topography Using Polarimetric SAR, Presented at IGARSS’95, 1995
[57] Hajnsek I, Cloude S R, Lee J S , et al. Inversion of surface parameters from polarimetric SAR data[C]. Presented at IGARSS 2000. Honolulu, Hawaii: 2000
[58] Hajnsek I., Pottier E., Cloude S. R.. Inversion of surface parameters from polarimetric SAR [J]. IEEE Trans.on Geoscience and Remote Sensing, 2003, 41(4):727-744
[59] Lee H., Chen K., Lee J., et al. A comparisons of model based and image based surface parametersestimation from polarimetric SAR[C]. Presented at IGARSS 2005. Seoul: 2005
[60] 王翠珍.极化 SAR 数据分析与目标信息提取[D].北京:中科院遥感所,1999
[61] 刘秀清.全极化合成孔径雷达极化信息处理技术研究[D].北京:中科院电子所,2004
[62] 徐俊毅.极化雷达遥感图像分类研究[D].北京:清华大学电子工程系,2002
[63] Novak L. M., Burl M. C.. Optimal speckle reduction in polarimetric SAR imagery [J]. IEEE Transactions on Aerospace and Electronic Systems, 1990, 26(2):293-305
[64] Lee J. S., Grunes M. R., Mango S. A.. Speckle reduction in multipolarization,multifrequency SAR imagery [J]. IEEE Trans. Remote Sensing, 1991, 29(4):535-544
[65] Lopes A., Goze S., Nezry E.. Polarimetric Speckle Filters For SAR Data[C]. Presented at IGARSS'92. Houston: 1992
[66] Lee J. S., Grunes M. R., Grandi. Polarimetric SAR speckle filtering and its implication for classification [J]. IEEE Trans.Geosci.Remote Sensing, 1999, 37(5):2363-2373
[67] Novak L. M., Burl M. C., Irving W.W., et al. Optimal polarimetric processing for enhanced target detection[C]. Presented at Telesystems Conference. NTC '91, 1991
[68] Novak L. M., Burl M. C., Irving W. W.. Optimal polarimetric processing for enhanced target detection [J]. IEEE Transaction on Areospace and Electronic Systems, 1993, 29(1):234-244
[69] Novak L. M.,Halversen S. D., Owirka G. J., et al. Effects of polarization and resolution on SAR ATR [J]. IEEE Transactions on Aerospace and Electronic Systems,1997, 33(1):102—116
[70] Andrew P., Robert R., Kotska O., et al. Land target detection using high resolution mufti-polarimetric SAR data [C]. IGARSS’98, Seattle, USA, 1998
[71] Lee J. S..Digital Image Enhancement and Noise Filtering by Use of Local Statistics[J].IEEE Tans.Pattern Analysis and Machine Intelligence,1980,PAMI-2(2):165-168
[72] Lee J. S., Grunes M. R., Grandi G. De. Polarimetric SAR speckle filtering and its impact on classification[C]. Presented at IGASS'97. Singapore: 1997
[73] Touzi R., Lopes A.. The principle of speckle filtering in polarimetric SAR imagery [J]. IEEE Trans. Geosci. Romote Sensing, 1994, 32(5):1110-1114
[74] 刘秀清,杨震,杨汝良.全极化合成孔径雷达图像极化白化滤波参数估计方法的改进研究[J].电子学报,2003,31(12):1795-1799
[75] Sang-Ho Yoon, Young-Soo Kim. Classified pixel-based windowing algorithm for polarimetric SAR speckle filtering[J]. Electronics Letters,2003,39(1):115-117
[76] 舒宁.微波遥感原理[M].1.武汉:武汉测绘大学出版社,2000
[77] Lopez-Martinez C., Ferro-Famil L., Pottier E.. Polarimetry Tutorial[EB]. http://eartch.esa.int:80/polsarpro/tutorial.html,2005
[78] Touzi R., Charbonneau F., Hawkins R. K. , et al. Ship-sea contrast optimization when using polarimetric SARs[C]. Presented at IGARSS '01. Sydney: 2001
[79] Dubois P. C., van Zyl J., Engman T.. Measuring soil moisture with imaging radars [J]. IEEE Trans. Geiosci. Remote Sensing, 1995, 33(4):915-926
[80] Borgeaud M., Nell J.. Comparisons Of Theoretical Surface Scattering Models For Polarimetric Microwave Remote Sensing[C]. Presented at IGARSS'92. 1992
[81] Borgeaud M., Noll J.. Analysis of theoretical surface scattering models for polarimetric microwave remote sensing of bare soils. International Journal of Remote Sensing,1994,15(14): 2931-2942
[82] Kozlov A. I., Ligthart L. P., Logvin A. I.. Mathematical and Physical Modelling of Microwave Scattering and Polarimetric Remote Sensing[M]. Boston: Kluwer Academic Publishers, 2001
[83]姚鲁.全极化 SAR 水面船只目标探测的研究[R].国家海洋局第二海洋研究所,2006
[84] Touzi R., Boerner W. M., Lee J. S. , et al. A review of polarimetry in the context of synthetic aperture radar: concepts and information extraction [J]. Can. J. Remote Sensing, 2004, 30(3):380-407
[85] Youan K.. Invariant characters on radar cross section of polarized radar targets[C]. IEEE International Conference on Radar, 2000
[86]郭德方.遥感图像的计算机处理和模式识别[M].北京:电子工业出版社,1987
[87]徐俊毅,杨健,彭应宁.极化雷达目标检测中的鉴别信息[C].第八界全国雷达学术年会交流论文.合肥:2002
[88]徐俊毅, 杨健, 彭应宁.相似性参数在极化雷达遥感图像分析中的作用[C].第八届全国雷达年会交流论文.合肥:2002
[89] 陈祖明,周家胜.矩阵论引论[M].北京:北京航空航天大学出版社,2000
[90] Wang wenguang, Wang Jun., Mao Shiyi. Classification of polarimetric SAR images based on difference degree[C]. Presented at EUSAR2006. Dresden: 2006
[91]王文光,王俊,毛士艺.一种基于差异度的极化 SAR 迭代分类方法[J].电子与信息学报,2006,28(11):2007-2010
[92] Inannidis G. A., Hamers D. E.. Optimum antenna polarizations for target discrimaination in clutter. IEEE trans. antennas propag., 1979, ap-27:357-363
[93] Kostinski A., Boerner W..on the Polarimetric Contrast Optimization[J]. IEEE Trans.on A.P., 1987, AP-35(8): 988-991
[94] 杨健,董贵威,彭应宁.广义相对最优极化及其应用[C].中国航空学会电子专业委员会 2003学术交流会交流论文.上海:2003
[95] Jian Y., Guiwei D., Yingning P. , et al. Generalized optimization of polarimetric contrast enhancement [J]. IEEE Geoscience and Remote Sensing Letters, 2004, 1(3):171-174
[96] Yang J., Yamaguchi Y., Yamada H..Co-null of targets and co-null Abelian group[J]. Electronics Letters, 1999, 35(12): 1017-1019
[97] Yang J., Yamaguchi Y., Yamada H. , et al. Development of target null theory [J]. IEEE Trans.Geosci.Remote Sensing, 2001, 39(2):330-338
[98] Cao Fang, Hong Wen, Wu Yirong. An improved cloude-pottier decomposition using H/α/span and complex wishart classifier for polarimetric SAR classification[C]. Presented at 2006 CIE international conference on radar. Shanghai: 2006
[99] 刘秀清,杨汝良.基于全极化 SAR 非监督分类的迭代分类方法[J].电子学报,2004,32(12):1982-1986
[100] Zhang Haijian,Yang Wen, Chen Jiayu , et al..Improved classification of polarimetric SAR data based on four-component scattering model[C]. Presented at 2006 CIE international conference on radar. Shanghai: 2006
[101] Yeremy M., Campbell J. W., Mattar K. , et al. Ocean surveillance with polarimetric SAR [J]. Can.J.Remote Sensing, 2001, 27(4):328-344
[102] 张宇,张永刚,黄韦艮.星载 SAR 船舶及尾迹探测技术研究[J].遥感技术与应用,2003,18(1):31-35
[103] 张宇,张永刚,黄韦艮,等.一种利用 SAR 图像检测船舶尾迹的方法[J].国土资源遥感,2003,(1):56-58
[104] Pottier E., Boerner W. M., Schuler D. L.. Polarimetric detection and estimation of ship wakes[C]. Presented at IGARSS'99. 1999
[105] 钟雪莲.SAR 图像中人造目标的检测和辨别[D].北京:中科院遥感应用研究所,2005
[106] Rey M.T., Tunaley J.K., Folinsbee J.T., et al.. Application of radon transform techniques to wake detection in Seasat-A SAR Images[J]. IEEE Trans.Geosci.Remote Sensing, 1990, 28(4): 553-560
[107] Copeland A.C., Ravichandran G., Trivedi M.M.. Localized Radon transform-based detection of ship wakes in SAR images[J]. IEEE Trans.Geosci.Remote Sensing, 1995, 33(1): 35-45
[108] Imbo P., Souyris J., Yeremy M.. Wake detection in polarimetric SAR images[C]. Presented at IGARSS'01. 2001
[109] Courmontagne P.. An improvement of ship wake detection based on the radon transform[J]. Signal Processing, 2005 , 85(8): 1634-1654