PolInSAR地表参数反演方法研究
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摘要
极化干涉合成孔径雷达(PolInSAR)集PolSAR和InSAR测量技术于一体,可以同时把目标的精细物理特征与空间分布特性结合起来。极化干涉测量不仅能够提高常规InSAR测量的精度,而且有助于更好的理解目标的散射机理和所发生的散射过程,进一步拓展了SAR在成像遥感领域的应用,在军事和民用领域具有无法估量的作用。PolInSAR可用于反演地表植被参数,特别是森林的高度参数。地表参数的提取为地表分类及进一步目标识别奠定了基础,因此用极化干涉雷达数据提取地表植被参数是当前极化干涉研究的热点问题。
论文主要研究了既有的PolInSAR植被高度反演方法,然后在此基础上提出了一种融合的植被高度反演算法,最后对极化相干层析(PCT)算法进行了初步的探讨。主要内容包括:极化干涉SAR相干最优理论,相干散射模型,单基线植被高度反演方法,基于DEM差分法和相干幅度法的融合反演算法,PCT算法。
本文首先对PolSAR的基本理论进行了阐述,包括目标极化散射特性的表征和基本极化散射机理。然后对PolInSAR技术中的复干涉相干系数和极化相干最优理论给出了详尽的推导和分析。最后对相干最优理论进行了仿真验证。
接下来,论文讨论了相干散射模型,重点研究了RVoG相干散射模型和相应的参数反演模型,并分析了模型中各个参数对干涉相干性的影响。
在对PolInSAR理论进行深入讨论后,论文研究了两种既有的经典的单基线反演方法(三阶段法和ESPRIT算法),在此基础上研究了ESPRIT算法的改进算法,同时提出了一种基于ESPRIT算法和相干幅度法的联合反演方法。利用仿真数据对这各种方法进行了验证和性能比较。
针对三阶段法和ESPRIT算法存在的问题,论文提出了一种基于DEM差分法和相干幅度法的融合反演方法,对其原理进行了详细的阐述,并利用PolInSAR仿真数据对此方法进行了仿真验证。
最后,对PCT算法进行了初步探讨,并利用仿真数据对其进行了验证。
Polarimetric SAR interferometry (PolInSAR) is the technique that integrates radar polarimetry and radar interferometry. The interferometric analysis of a full coherent polarimetric data set enables the combination of final structure properties and spatial information of the targets. PolInSAR is a potential technique that not only improves the accuracy of the interferometric measurements but also allows a more sophisticated physical interpretation of scattering mechanism. With lots of advantages in many areas of military, civil and scientific researches, PolInSAR has extented the applications of SAR remote sensing, and has wide and latent prospective applications and valuable researching aspects.PolInSAR has been used to invert vegetation parameters of terrain surface, especially for height of forest. These parameters are the bases of terrain classification and target detection and recognition. Therefore, terrain surface vegetation parameters inversion using PolInSAR data has been hot research topics in polarimetric interferometry in recent years.
The dissertation mainly analyses and studies the established terrain surface vegetation parameters inversion methods for PolInSAR, on basis of these methods, the dissertation proposes a fast and robust vegetation height inversion method. The main contents include Polarimetric Interferometric Phase Coherence Optimization(PIPCO); Random Volume over Ground (RVoG) coherence scattering model and corresponding inversion model; single baseline vegetation height inversion method; vegetation height inversion method based on the fusion of DEM differencing algorithm and Coherence Amplitude algorithm; Polarimetric Coherence Tomography algorithm.
Firstly, this dissertation provides an overview of basic theory of PolSAR, such as representation of polarimetric scattering characters of targets and elementary scattering mechanisms. Then the calculation of complex coherence coefficient and the theory of PIPCO for PolInSAR are discussed comprehensively. Furthermore, the theory of PIPCO is validated by simulated data.
Secondly, coherence scattering models are studied. The study is focused on the RVoG scattering model and corresponding inversion model. The influences upon coherence of all the parameters in the model are discussed.
Thirdly, after in-depth discussion of theory of PolInSAR, two existed and classical single baseline inversion methods (the Three-Stage method and the ESPRIT algorithm) are studied, on the basis of it, an improved ESPRIT algorithm is studies, and a hybird vegetation height inversion method based on the ESPRIT algorithm and Coherence Amplitude method is proposed. these methods are validated by simulated data and the performance of them is compared.
For the questions of exist in the Three-Stage method and the ESPRIT algorithm, the dissertation proposes a kind of inversion method based on the fusion of DEM differencing algorithm and Coherence Amplitude method, the principles of it are discussed comprehensively, and the simulated PolInSAR data are used to validate the proposed method.
Finally, the dissertation analyses and studies PCT algorithm, and the simulated data are used to validate this algorithm.
论文主要研究了既有的PolInSAR植被高度反演方法,然后在此基础上提出了一种融合的植被高度反演算法,最后对极化相干层析(PCT)算法进行了初步的探讨。主要内容包括:极化干涉SAR相干最优理论,相干散射模型,单基线植被高度反演方法,基于DEM差分法和相干幅度法的融合反演算法,PCT算法。
本文首先对PolSAR的基本理论进行了阐述,包括目标极化散射特性的表征和基本极化散射机理。然后对PolInSAR技术中的复干涉相干系数和极化相干最优理论给出了详尽的推导和分析。最后对相干最优理论进行了仿真验证。
接下来,论文讨论了相干散射模型,重点研究了RVoG相干散射模型和相应的参数反演模型,并分析了模型中各个参数对干涉相干性的影响。
在对PolInSAR理论进行深入讨论后,论文研究了两种既有的经典的单基线反演方法(三阶段法和ESPRIT算法),在此基础上研究了ESPRIT算法的改进算法,同时提出了一种基于ESPRIT算法和相干幅度法的联合反演方法。利用仿真数据对这各种方法进行了验证和性能比较。
针对三阶段法和ESPRIT算法存在的问题,论文提出了一种基于DEM差分法和相干幅度法的融合反演方法,对其原理进行了详细的阐述,并利用PolInSAR仿真数据对此方法进行了仿真验证。
最后,对PCT算法进行了初步探讨,并利用仿真数据对其进行了验证。
Polarimetric SAR interferometry (PolInSAR) is the technique that integrates radar polarimetry and radar interferometry. The interferometric analysis of a full coherent polarimetric data set enables the combination of final structure properties and spatial information of the targets. PolInSAR is a potential technique that not only improves the accuracy of the interferometric measurements but also allows a more sophisticated physical interpretation of scattering mechanism. With lots of advantages in many areas of military, civil and scientific researches, PolInSAR has extented the applications of SAR remote sensing, and has wide and latent prospective applications and valuable researching aspects.PolInSAR has been used to invert vegetation parameters of terrain surface, especially for height of forest. These parameters are the bases of terrain classification and target detection and recognition. Therefore, terrain surface vegetation parameters inversion using PolInSAR data has been hot research topics in polarimetric interferometry in recent years.
The dissertation mainly analyses and studies the established terrain surface vegetation parameters inversion methods for PolInSAR, on basis of these methods, the dissertation proposes a fast and robust vegetation height inversion method. The main contents include Polarimetric Interferometric Phase Coherence Optimization(PIPCO); Random Volume over Ground (RVoG) coherence scattering model and corresponding inversion model; single baseline vegetation height inversion method; vegetation height inversion method based on the fusion of DEM differencing algorithm and Coherence Amplitude algorithm; Polarimetric Coherence Tomography algorithm.
Firstly, this dissertation provides an overview of basic theory of PolSAR, such as representation of polarimetric scattering characters of targets and elementary scattering mechanisms. Then the calculation of complex coherence coefficient and the theory of PIPCO for PolInSAR are discussed comprehensively. Furthermore, the theory of PIPCO is validated by simulated data.
Secondly, coherence scattering models are studied. The study is focused on the RVoG scattering model and corresponding inversion model. The influences upon coherence of all the parameters in the model are discussed.
Thirdly, after in-depth discussion of theory of PolInSAR, two existed and classical single baseline inversion methods (the Three-Stage method and the ESPRIT algorithm) are studied, on the basis of it, an improved ESPRIT algorithm is studies, and a hybird vegetation height inversion method based on the ESPRIT algorithm and Coherence Amplitude method is proposed. these methods are validated by simulated data and the performance of them is compared.
For the questions of exist in the Three-Stage method and the ESPRIT algorithm, the dissertation proposes a kind of inversion method based on the fusion of DEM differencing algorithm and Coherence Amplitude method, the principles of it are discussed comprehensively, and the simulated PolInSAR data are used to validate the proposed method.
Finally, the dissertation analyses and studies PCT algorithm, and the simulated data are used to validate this algorithm.
引文
[1] S.R.Cloude, K.P.Papathanassiou. Polarimetric SAR Interferometry. IEEE Trans. on GRS, 1998, 36(5):1551-1565
[2] 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. Proc. of the CEOS SAR Workshop, Toulouse, 26-29 Oct. 1999:347-358
[3] R.N.Treuhaft, S.N.Madsen, M.Moghaddam, et al. Vegetation Characteristics and Surface Topography from Interferometric Radar. Radio Science, 1996, 31:1449-1485
[4] R.N.Treuhaft, S.R.Cloude. The Structure of Oriented Vegetation from Polarimetric Interferometry. IEEE Trans. on GRS, 1999, 37(5): 2620-2624
[5] R.N.Treuhaft. Vertical Structure of Vegetated Land Surfaces from Interferometric and Polarimetric Radar. Radio Sciences, 2000, 35(1):141-177
[6] K.P.Papathanassiou, S.R.Cloude. Single-baseline Polarimetric SAR Interferometry. IEEE Trans. on GRS, 2001,39(11):2352-2363
[7] M.Isola, S.R.Cloude. Forest Height Mapping using Spaceborne Polarimetric SAR Interferometry. Proc. of IGARSS'O1,Sydney, Australia, 9-13 July 2001, 3:1095-1097
[8] S.R.Cloude, K.P.Papathanassiou. A 3-Stage Inversion Process for Polarimetric SAR Interferometry. Proc. of EUSAR'02, Cologne.Germany, 4-6 June 2002:297-282
[9] S.R.Cloude, K.P.Papathanassiou. Three-stage Inversion Process for Polarimetric SAR Interferometry. IEE Proc. Radar Sonar Navig, 2003, 150(3):125-134
[10] M.Qong. Polarization State Conformation and its Application to Change Detection in PolSAR. IEEE GRSL, Oct. 2004, 1(4):304-308
[11] M.Qong. A New Polarization State Conformation and its Application to Coherence Optimization in PolInSAR. Proc. of IGARSS'04, Anchorage, Alaska, 20-24 Sept. 2004, 4:2495-2498
[12] M.Qong. Coherence Optimization using the Polarization Conformation in PolInSAR. IEEE GRSL, July 2005, 2(3):301-305
[13] J.L.Gomez-Dans, S.Quegan. Constraining Coherence Optimisation in Polarimetric Interferometry of Layered Targets. Proc. of PolInSAR 2005, Frascati, Italy, 17-21 Jan. 2005:1-6
[14] M.Neumann,L.Ferro-Famil,A.Reigber. Multibaseline POLInSAR coherence modelling and optimization. Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International,23-28 July 2007,2624 - 2627
[15] K.P.Papathanassiou, T.Mette, LHajnsek. Model Based Forest Height Estimation from Single Baseline PolInSAR Data: The Fichtelgebirge Test Case. Proc. of PolInSAR 2003, Frascati, Italy, 14-16 Jan. 2003:1-6
[16] L.Sagues, X.Fabregas, A.Broquetas. Extraction of Vegetation Structure and Surface Parameters Using Polarimetric and Interferometric SAR Techniques. Proc. of IGARSS'00, Honolulu, Hawaii, 24-28 July 2000, 1:141-143
[17] T.Flynn, M.Tabb, R.Carande. Direction Estimation of Vegetation Parameters from Covariance Data in Polarimetric SAR Interferometry. Proc. of IGARSS'02, Toronto, Canada, 24-28 June 2002, 3:1908-1910
[18] M.Tabb, T.Flynn, R.Carande. Full Maximum Likelihood Inversion of PolInSAR Scattering Models. Proc. of IGARSS'04, Anchorage, Alaska, 20-24 Sept. 2004, 2:1232-1235
[19] E.Colin, W.Tabbara, A.Reigber. Polarimetric Interferometry and Time-Frequency Analysis Applied to A Urban Area at X-band. Proc. Of IGARSS'05, Seoul, Korea, 25-29 July 2005, 2:1077-1080
[20] M.Qong, A.Iwashita. Estimation of Forest Height and Forested Area with Polarimetric SAR Interferometry. Proc. of IGARSS'05, Seoul, Korea, 25-29 July 2005 ,8:5520-5522
[21] A.Liseno, K.P.Papathanassiou, A.Moreira, R.Pierri. Analysis of Forest Parameters SAR Inversion from SLC Multibaseline Data. Proc. of PoIInSAR 2005, Frascati, Italy, 17-21 Jan. 2005:100-105
[22] F.Garestier, LChampion, P.Dubois-Fernandez, et al. Polar and PolInSAR Analysis of Pine Forest at L and P Band on High Resolution Data. Proc. of IGARSS'05, Seoul, Korea, 25-29 July 2005, 2:1093-1096
[23] H.Yamada, Y.Yamaguchi, et al. Polarimetric SAR Interferometry for Forest Analysis Based on the ESPRIT Algorithm. IEICE Trans. Electron, 2001,E84-C(12):1917- 1924
[24] H.Yamada, K.Sato, Y.Yamaguchi, et al. Interferometric Phase and Coherence of Forest Estimated by ESPRIT-based Polarimetric SAR Interferometry. Proc. of IGARSS'02, Toronto,Canada, 24-28 June 2002, 2:829-831
[25] H.Yamada, Y.Yamaguchi, W.M.Boerner. Forest Height Feature Extraction in Polarimetric SAR Interferometry by using Rotational Invariance Property. Proc. of IEEE IGARSS'03,Toulouse, France, 21-25, July 2003, 3:1426-1428.
[26] H.Yamada, H.Okada, Y.Yamaguchi. Accuracy Improvement of ESPRIT based Polarimetric SAR Interferometry for Forest Height Estimation. Proc. of IGARSS'05, Seoul, Korea, 25-29 July 2005, 6:4077-4080
[27] S.Guillaso, L.Ferro-Famil, A.Reigber, et al. Polarimetric Interferometric SAR Data Analysis Based on ESPRIT/MUSIC Methods. Proc. of PolInSAR 2003, Frascati, Italy, 14-16 Jan. 2003:1-6
[28] S.Guillaso, L.Ferro-Famil A.Reigber, et al. Urban Area Analysis Based on ESPRIT/MUSIC Mothods using Polarimetric Interferometric SAR. Proc. of 2nd GRSS/ISPRS joint Workshop on "Data Fusion and Remote Sensing over Urban Areas" Technical University of Berlin, 22-23 May 2003:77-81
[29] S.Guillaso, A.Reigber, L.Ferro-Famil. Evaluation of the ESPRIT Approach in Polarimetric Interferometric SAR. Proc. of IGARSS'05, Seoul, Korea, 25-29 July 2005, 1:1-4
[30]杨震,杨汝良.极化合成孔径雷达干涉技术.遥感技术与应用,2001,16(3):139-143
[31]杨震.合成孔径雷达干涉与极化干涉技术研究.中国科学院电子学研究所博士学位论文,2003:67-97
[32] Z.Yang, R.Yang. Application of Polarimetric Synthetic Aperture Radar Interferometry for Land Cover Classification. Proc. of IEEE on Radar Conference. 22-25 April 2002:459-463
[33]郭华东,李新武等.极化干涉雷达遥感机制及应用.遥感学报,2002,6(6): 401-401
[34]李新武.极化干涉SAR信息提取方法及其应用研究.中科院遥感应用研究所博士学位论文,2002:105-116
[35]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
[36] X.Li, H.Guo. Generation and Error Analysis of DEM using Spaceborne Polarimetric SAR Interferometry Data. Proc. of IGARSS'02, Toronto, Canada, 24-28 June 2002, 5:2705-2707
[37]李新武,郭华东等.极化干涉SAR数据地表土地类型分类.遥感学报,2002,6(6):507-510
[38] H.Zhang, C.Wang, Z.Liu. Polarimetric SAR Interferometry for Vegetable Vertical Structure Parameters Extraction. Proc. of IGARSS'02, Toronto, Canada, 24-28 June 2002, 5:2611-2613
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[47] M.Tabb, J.Orrey, T.Flynn, et al. Phase Diversity: A Decomposition for Vegetation Parameter Estimation using Polarimetric SAR Interferometry, Proceedings of 4th European Synthetic Aperture Radar Conference, EUSAR 2002, pp 721-724
[2] 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. Proc. of the CEOS SAR Workshop, Toulouse, 26-29 Oct. 1999:347-358
[3] R.N.Treuhaft, S.N.Madsen, M.Moghaddam, et al. Vegetation Characteristics and Surface Topography from Interferometric Radar. Radio Science, 1996, 31:1449-1485
[4] R.N.Treuhaft, S.R.Cloude. The Structure of Oriented Vegetation from Polarimetric Interferometry. IEEE Trans. on GRS, 1999, 37(5): 2620-2624
[5] R.N.Treuhaft. Vertical Structure of Vegetated Land Surfaces from Interferometric and Polarimetric Radar. Radio Sciences, 2000, 35(1):141-177
[6] K.P.Papathanassiou, S.R.Cloude. Single-baseline Polarimetric SAR Interferometry. IEEE Trans. on GRS, 2001,39(11):2352-2363
[7] M.Isola, S.R.Cloude. Forest Height Mapping using Spaceborne Polarimetric SAR Interferometry. Proc. of IGARSS'O1,Sydney, Australia, 9-13 July 2001, 3:1095-1097
[8] S.R.Cloude, K.P.Papathanassiou. A 3-Stage Inversion Process for Polarimetric SAR Interferometry. Proc. of EUSAR'02, Cologne.Germany, 4-6 June 2002:297-282
[9] S.R.Cloude, K.P.Papathanassiou. Three-stage Inversion Process for Polarimetric SAR Interferometry. IEE Proc. Radar Sonar Navig, 2003, 150(3):125-134
[10] M.Qong. Polarization State Conformation and its Application to Change Detection in PolSAR. IEEE GRSL, Oct. 2004, 1(4):304-308
[11] M.Qong. A New Polarization State Conformation and its Application to Coherence Optimization in PolInSAR. Proc. of IGARSS'04, Anchorage, Alaska, 20-24 Sept. 2004, 4:2495-2498
[12] M.Qong. Coherence Optimization using the Polarization Conformation in PolInSAR. IEEE GRSL, July 2005, 2(3):301-305
[13] J.L.Gomez-Dans, S.Quegan. Constraining Coherence Optimisation in Polarimetric Interferometry of Layered Targets. Proc. of PolInSAR 2005, Frascati, Italy, 17-21 Jan. 2005:1-6
[14] M.Neumann,L.Ferro-Famil,A.Reigber. Multibaseline POLInSAR coherence modelling and optimization. Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International,23-28 July 2007,2624 - 2627
[15] K.P.Papathanassiou, T.Mette, LHajnsek. Model Based Forest Height Estimation from Single Baseline PolInSAR Data: The Fichtelgebirge Test Case. Proc. of PolInSAR 2003, Frascati, Italy, 14-16 Jan. 2003:1-6
[16] L.Sagues, X.Fabregas, A.Broquetas. Extraction of Vegetation Structure and Surface Parameters Using Polarimetric and Interferometric SAR Techniques. Proc. of IGARSS'00, Honolulu, Hawaii, 24-28 July 2000, 1:141-143
[17] T.Flynn, M.Tabb, R.Carande. Direction Estimation of Vegetation Parameters from Covariance Data in Polarimetric SAR Interferometry. Proc. of IGARSS'02, Toronto, Canada, 24-28 June 2002, 3:1908-1910
[18] M.Tabb, T.Flynn, R.Carande. Full Maximum Likelihood Inversion of PolInSAR Scattering Models. Proc. of IGARSS'04, Anchorage, Alaska, 20-24 Sept. 2004, 2:1232-1235
[19] E.Colin, W.Tabbara, A.Reigber. Polarimetric Interferometry and Time-Frequency Analysis Applied to A Urban Area at X-band. Proc. Of IGARSS'05, Seoul, Korea, 25-29 July 2005, 2:1077-1080
[20] M.Qong, A.Iwashita. Estimation of Forest Height and Forested Area with Polarimetric SAR Interferometry. Proc. of IGARSS'05, Seoul, Korea, 25-29 July 2005 ,8:5520-5522
[21] A.Liseno, K.P.Papathanassiou, A.Moreira, R.Pierri. Analysis of Forest Parameters SAR Inversion from SLC Multibaseline Data. Proc. of PoIInSAR 2005, Frascati, Italy, 17-21 Jan. 2005:100-105
[22] F.Garestier, LChampion, P.Dubois-Fernandez, et al. Polar and PolInSAR Analysis of Pine Forest at L and P Band on High Resolution Data. Proc. of IGARSS'05, Seoul, Korea, 25-29 July 2005, 2:1093-1096
[23] H.Yamada, Y.Yamaguchi, et al. Polarimetric SAR Interferometry for Forest Analysis Based on the ESPRIT Algorithm. IEICE Trans. Electron, 2001,E84-C(12):1917- 1924
[24] H.Yamada, K.Sato, Y.Yamaguchi, et al. Interferometric Phase and Coherence of Forest Estimated by ESPRIT-based Polarimetric SAR Interferometry. Proc. of IGARSS'02, Toronto,Canada, 24-28 June 2002, 2:829-831
[25] H.Yamada, Y.Yamaguchi, W.M.Boerner. Forest Height Feature Extraction in Polarimetric SAR Interferometry by using Rotational Invariance Property. Proc. of IEEE IGARSS'03,Toulouse, France, 21-25, July 2003, 3:1426-1428.
[26] H.Yamada, H.Okada, Y.Yamaguchi. Accuracy Improvement of ESPRIT based Polarimetric SAR Interferometry for Forest Height Estimation. Proc. of IGARSS'05, Seoul, Korea, 25-29 July 2005, 6:4077-4080
[27] S.Guillaso, L.Ferro-Famil, A.Reigber, et al. Polarimetric Interferometric SAR Data Analysis Based on ESPRIT/MUSIC Methods. Proc. of PolInSAR 2003, Frascati, Italy, 14-16 Jan. 2003:1-6
[28] S.Guillaso, L.Ferro-Famil A.Reigber, et al. Urban Area Analysis Based on ESPRIT/MUSIC Mothods using Polarimetric Interferometric SAR. Proc. of 2nd GRSS/ISPRS joint Workshop on "Data Fusion and Remote Sensing over Urban Areas" Technical University of Berlin, 22-23 May 2003:77-81
[29] S.Guillaso, A.Reigber, L.Ferro-Famil. Evaluation of the ESPRIT Approach in Polarimetric Interferometric SAR. Proc. of IGARSS'05, Seoul, Korea, 25-29 July 2005, 1:1-4
[30]杨震,杨汝良.极化合成孔径雷达干涉技术.遥感技术与应用,2001,16(3):139-143
[31]杨震.合成孔径雷达干涉与极化干涉技术研究.中国科学院电子学研究所博士学位论文,2003:67-97
[32] Z.Yang, R.Yang. Application of Polarimetric Synthetic Aperture Radar Interferometry for Land Cover Classification. Proc. of IEEE on Radar Conference. 22-25 April 2002:459-463
[33]郭华东,李新武等.极化干涉雷达遥感机制及应用.遥感学报,2002,6(6): 401-401
[34]李新武.极化干涉SAR信息提取方法及其应用研究.中科院遥感应用研究所博士学位论文,2002:105-116
[35]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
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