分布式星载InSAR与SAR-GMTI信号处理研究
|
摘要
分布式星载合成孔径雷达(SAR)是将卫星编队和星载SAR技术有机结合的新体制航天雷达系统。它通过多颗卫星编队飞行、协同工作,可实现干涉测高(InSAR)功能,使得快速、大范围地获取高精度DEM数据成为可能;可实现地面运动目标指示(GMTI)功能,为地表大面积监视、侦察和目标跟踪、定位提供了可能。该类系统具有重要的军事和民用价值,是目前国内外研究的热点。
在提高性能的同时,分布式星载SAR在系统理论和技术上也存在诸多难点,面临许多挑战,需要新的系统设计理论及信号处理技术予以支撑。本文瞄准分布式星载InSAR和SAR-GMTI信号处理这一前沿课题,对分布式星载InSAR单/多基线信号处理方法和分布式星载SAR-GMTI单/多基线信号处理方法展开研究。论文各章节的研究内容安排如下:
第二章研究了分布式星载InSAR单基线信号处理方法。首先,针对在复杂地形区域,星间长基线会导致干涉相位条纹密集、随机噪声增强的问题,提出了一种自适应多分辨率干涉相位滤波方法。该方法能有效地适应干涉相位二维空变特性,兼顾了抑制相位噪声和保持条纹细节间良好的综合性能,为获取高质量的DEM打下了基础。其次,提出了一种单基线InSAR叠掩和阴影区域检测方法。从叠掩和阴影区域的几何模型与信号模型出发,分析了叠掩、阴影和正常InSAR区域干涉信号相关矩阵的特点,提出了基于信息论的叠掩和阴影区域检测方法,在InSAR干涉相位中将叠掩和阴影区域隔离出来,保证了后续处理步骤的有效性和可靠性。
第三章研究了分布式星载InSAR的多基线信号处理方法。以多星编队InSAR系统单航过为背景,研究了多基线条件下的叠掩、阴影和正常InSAR干涉区域的检测方法,以及叠掩区域的叠加信号个数估计、干涉相位估计和解缠方法。首先,采用基于信息论的干涉相位区域分类方法,将InSAR干涉区域分为叠掩、阴影和正常InSAR干涉区域,并估计出叠掩区域所包含的来自不同地面区域的信号个数。其次,研究了基于Root-MUSIC和RELAX的叠掩区域干涉相位估计与解缠方法,对叠掩区域中来自不同地面区域的信号分别进行相位估计和解缠。
第四章研究了分布式星载SAR-GMTI单基线信号处理方法。首先,以双星单相位中心SAR-GMTI系统为背景,基于杂波和动目标的信号模型及统计分布模型,考虑杂波和加性噪声、通道幅度/相位不一致性误差、频率同步误差等影响因素,分析了SAR-ATI和SAR-DPCA技术的运动目标检测性能。其次,针对SAR-ATI技术的恒虚警检测问题,以“杂波”和“杂波+动目标”的幅相二维联合分布为基础,证实了选取幅度作为一维检测子的可行性,研究了相位单边、幅度单边和幅-相二级恒虚警检测方法;提出了基于条件分布的幅度-相位二级恒虚警检测方法和幅度-相位二维联合的恒虚警检测方法,并以基于NP准则的似然比检测方法的性能为上限,对以上恒虚警检测方法性能进行了分析和对比。最后,针对分布式星载单基线SAR-GMTI系统存在的混合基线问题,在地面场景为平地情况下,提出了修正的SAR-DPCA和SAR-ATI方法;在地面场景为起伏山区情况下,提出了一种自适应SAR-DPCA杂波抑制方法,取得了令人满意的结果。
第五章提出了稳健的多基线SAR-GMTI自适应杂波抑制、运动目标检测、测速和重定位方法。首先,分析了分布式星载SAR-GMTI多基线信号处理中,杂波图像间去相关和运动目标导向矢量失配这两种重要的误差源,采用了对角加载技术和基于地面道路先验信息的动目标导向矢量估计技术,有效地抑制了这两类误差。其次,提出了基于地面道路先验信息的二元假设和多元假设恒虚警检测方法。再次,提出了一种基于地面道路先验信息的动目标测速和重定位方法,提高了估计精度,降低了运算量。
第六章总结了全文主要工作、创新点及有待深入研究的问题。
Distributed spaceborne SAR system is a novel spaceborne radar system combining satellite formation flying technology and spaceborne SAR technology perfectly. Through formation flying and cooperation of several satellites, the system utilize Interferometric SAR to measure the large-scale terrain digital elevation model(DEM) with high precision. Ground Moving Target Indication (GMTI) of distributed spaceborne SAR system gives the opportunity for large scale surveillance, spying, and target tracking, position. Because of its special value for military and civil application, the distributed spaceborne SAR system is currently one of the research focuses all around the world.
The spaceborne SAR system faces a lot of system theory and technique challenges as well as it improves the performance. Since the system is a multilevel and complex large-scale system concerning broad technology, the novel system design theory and signal processing technique need to be studied to resolve the difficulties in the key techniques. This thesis focuses on the signal processing technique of InSAR and SAR-GMTI of the distributed spaceborne SAR system. The systematic research is carried out in single-baseline and multi-baseline signal processing technique of InSAR and SAR-GMTI in the paper. The research in each chapter is arranged as following:
In chapter 2, the single-baseline signal processing techniques of the distributed spaceborne InSAR system are studied. Firstly, an adaptive multiresolution filtering approach for interferometric phase is proposed. In the complicate topographic fields, the long baseline between the two satellites makes the interferometric fringe densely and increases the dispersion of the phase noise. The proposed method can track the phase 2-D changes more accurately and achieve a better attention to removal of the noise and preservation of the topographic details. Secondly, a layover and shadow detection method is proposed for single-baseline InSAR. From the geometrical model and signal model of layover and shadow, the thesis proposed a layover and shadow fields detection technique based on the information theoretic criteria. The layover and shadow fields are separated from the interferometric phase to ensure the validity and reliability of the following processing steps.
In chapter 3, the multi-baseline signal processing techniques of the distributed spaceborne InSAR system are studied. Based on the distributed spaceborne multi-baseline InSAR system, we study the detection of layover fields, the estimation of the number of the signal component, the estimation of interferometric phase and phase unwrapping. Firstly, based on the information theoretic criteria method, layover and shadow are isolated from the ordinary interferometric phase fields, and the number of the signal component in the layover fields are estimated. Secondly, interferometric phase estimation and phase unwrapping are studied based on Root-MUSIC and RELAX. In the layover fields, the signal from different fields are separated. Phase unwrapping are carried out in the ordinary interferometric phase fields and the layover fields separately.
In chapter 4, the single-baseline signal processing techniques of the distributed spaceborne SAR-GMTI system are studied. Firstly, based on the signal model and statistical model of the two clutter cancellers, the detection performance of SAR-ATI and SAR-DPCA are analyzed and compared, with consideration to the channel amplitude-phase unbalance error, time/frequency synchronization error and the influence of clutter and noise. Secondly, based on the joint probability density function (PDF) of interferogram’s phase and amplitude of the two hypotheses“clutter”and“clutter plus signal”, the one-step constant false alarm rate(CFAR) detector with interferometric phase or amplitude and the two-step CFAR detector with marginal PDF of interferometric phase or amplitude are analyzed for their capabilities and limitations. A new two-step CFAR detector with conditional PDF and a new two-dimensional CFAR detector are proposed. The likelihood ratio test based on the Neyman-Pearson(NP) criterion is exploited as an upper bound for the performance of the above CFAR detectors. Lastly, the clutter suppression technique are studied based on distributed spaceborne SAR-GMTI system, which includes hybrid along-track and cross-track baseline. When the ground scenes are flat earth, the modified SAR-DPCA and SAR-ATI technique are proposed. When the ground scenes are fluctuant mountainous area, an adaptive SAR-DPCA technique is proposed to settle the problem under some conditions.
In chapter 5, we proposed a robust optimum adaptive clutter suppression, moving targets detection, velocity measurement and target relocation technique for distributed spaceborne multi-baseline SAR-GMTI systems. Firstly, Some realistic problems related to the implementation of the processor are investigated, which include system multiplicative phase noise and steering vector mismatch. The diagonally loading techniques is resorted to improve the estimation of clutter statistics in the presence of multiplicative noise. A prior information, like road network information, is integrated into the optimum adaptive processor to reduce moving target steering vector mismatch. Secondly, two hypotheses and multiple hypotheses CFAR testing technique are proposed, which are based on the prior information of road network. Lastly, based on a priori information, the target velocity measurement and relocation technique are proposed, which improve the estimation accuracy with low computation load.
In chapter 6, we summarize the major work of the thesis, the innovation point and the problems needs to be improved.
在提高性能的同时,分布式星载SAR在系统理论和技术上也存在诸多难点,面临许多挑战,需要新的系统设计理论及信号处理技术予以支撑。本文瞄准分布式星载InSAR和SAR-GMTI信号处理这一前沿课题,对分布式星载InSAR单/多基线信号处理方法和分布式星载SAR-GMTI单/多基线信号处理方法展开研究。论文各章节的研究内容安排如下:
第二章研究了分布式星载InSAR单基线信号处理方法。首先,针对在复杂地形区域,星间长基线会导致干涉相位条纹密集、随机噪声增强的问题,提出了一种自适应多分辨率干涉相位滤波方法。该方法能有效地适应干涉相位二维空变特性,兼顾了抑制相位噪声和保持条纹细节间良好的综合性能,为获取高质量的DEM打下了基础。其次,提出了一种单基线InSAR叠掩和阴影区域检测方法。从叠掩和阴影区域的几何模型与信号模型出发,分析了叠掩、阴影和正常InSAR区域干涉信号相关矩阵的特点,提出了基于信息论的叠掩和阴影区域检测方法,在InSAR干涉相位中将叠掩和阴影区域隔离出来,保证了后续处理步骤的有效性和可靠性。
第三章研究了分布式星载InSAR的多基线信号处理方法。以多星编队InSAR系统单航过为背景,研究了多基线条件下的叠掩、阴影和正常InSAR干涉区域的检测方法,以及叠掩区域的叠加信号个数估计、干涉相位估计和解缠方法。首先,采用基于信息论的干涉相位区域分类方法,将InSAR干涉区域分为叠掩、阴影和正常InSAR干涉区域,并估计出叠掩区域所包含的来自不同地面区域的信号个数。其次,研究了基于Root-MUSIC和RELAX的叠掩区域干涉相位估计与解缠方法,对叠掩区域中来自不同地面区域的信号分别进行相位估计和解缠。
第四章研究了分布式星载SAR-GMTI单基线信号处理方法。首先,以双星单相位中心SAR-GMTI系统为背景,基于杂波和动目标的信号模型及统计分布模型,考虑杂波和加性噪声、通道幅度/相位不一致性误差、频率同步误差等影响因素,分析了SAR-ATI和SAR-DPCA技术的运动目标检测性能。其次,针对SAR-ATI技术的恒虚警检测问题,以“杂波”和“杂波+动目标”的幅相二维联合分布为基础,证实了选取幅度作为一维检测子的可行性,研究了相位单边、幅度单边和幅-相二级恒虚警检测方法;提出了基于条件分布的幅度-相位二级恒虚警检测方法和幅度-相位二维联合的恒虚警检测方法,并以基于NP准则的似然比检测方法的性能为上限,对以上恒虚警检测方法性能进行了分析和对比。最后,针对分布式星载单基线SAR-GMTI系统存在的混合基线问题,在地面场景为平地情况下,提出了修正的SAR-DPCA和SAR-ATI方法;在地面场景为起伏山区情况下,提出了一种自适应SAR-DPCA杂波抑制方法,取得了令人满意的结果。
第五章提出了稳健的多基线SAR-GMTI自适应杂波抑制、运动目标检测、测速和重定位方法。首先,分析了分布式星载SAR-GMTI多基线信号处理中,杂波图像间去相关和运动目标导向矢量失配这两种重要的误差源,采用了对角加载技术和基于地面道路先验信息的动目标导向矢量估计技术,有效地抑制了这两类误差。其次,提出了基于地面道路先验信息的二元假设和多元假设恒虚警检测方法。再次,提出了一种基于地面道路先验信息的动目标测速和重定位方法,提高了估计精度,降低了运算量。
第六章总结了全文主要工作、创新点及有待深入研究的问题。
Distributed spaceborne SAR system is a novel spaceborne radar system combining satellite formation flying technology and spaceborne SAR technology perfectly. Through formation flying and cooperation of several satellites, the system utilize Interferometric SAR to measure the large-scale terrain digital elevation model(DEM) with high precision. Ground Moving Target Indication (GMTI) of distributed spaceborne SAR system gives the opportunity for large scale surveillance, spying, and target tracking, position. Because of its special value for military and civil application, the distributed spaceborne SAR system is currently one of the research focuses all around the world.
The spaceborne SAR system faces a lot of system theory and technique challenges as well as it improves the performance. Since the system is a multilevel and complex large-scale system concerning broad technology, the novel system design theory and signal processing technique need to be studied to resolve the difficulties in the key techniques. This thesis focuses on the signal processing technique of InSAR and SAR-GMTI of the distributed spaceborne SAR system. The systematic research is carried out in single-baseline and multi-baseline signal processing technique of InSAR and SAR-GMTI in the paper. The research in each chapter is arranged as following:
In chapter 2, the single-baseline signal processing techniques of the distributed spaceborne InSAR system are studied. Firstly, an adaptive multiresolution filtering approach for interferometric phase is proposed. In the complicate topographic fields, the long baseline between the two satellites makes the interferometric fringe densely and increases the dispersion of the phase noise. The proposed method can track the phase 2-D changes more accurately and achieve a better attention to removal of the noise and preservation of the topographic details. Secondly, a layover and shadow detection method is proposed for single-baseline InSAR. From the geometrical model and signal model of layover and shadow, the thesis proposed a layover and shadow fields detection technique based on the information theoretic criteria. The layover and shadow fields are separated from the interferometric phase to ensure the validity and reliability of the following processing steps.
In chapter 3, the multi-baseline signal processing techniques of the distributed spaceborne InSAR system are studied. Based on the distributed spaceborne multi-baseline InSAR system, we study the detection of layover fields, the estimation of the number of the signal component, the estimation of interferometric phase and phase unwrapping. Firstly, based on the information theoretic criteria method, layover and shadow are isolated from the ordinary interferometric phase fields, and the number of the signal component in the layover fields are estimated. Secondly, interferometric phase estimation and phase unwrapping are studied based on Root-MUSIC and RELAX. In the layover fields, the signal from different fields are separated. Phase unwrapping are carried out in the ordinary interferometric phase fields and the layover fields separately.
In chapter 4, the single-baseline signal processing techniques of the distributed spaceborne SAR-GMTI system are studied. Firstly, based on the signal model and statistical model of the two clutter cancellers, the detection performance of SAR-ATI and SAR-DPCA are analyzed and compared, with consideration to the channel amplitude-phase unbalance error, time/frequency synchronization error and the influence of clutter and noise. Secondly, based on the joint probability density function (PDF) of interferogram’s phase and amplitude of the two hypotheses“clutter”and“clutter plus signal”, the one-step constant false alarm rate(CFAR) detector with interferometric phase or amplitude and the two-step CFAR detector with marginal PDF of interferometric phase or amplitude are analyzed for their capabilities and limitations. A new two-step CFAR detector with conditional PDF and a new two-dimensional CFAR detector are proposed. The likelihood ratio test based on the Neyman-Pearson(NP) criterion is exploited as an upper bound for the performance of the above CFAR detectors. Lastly, the clutter suppression technique are studied based on distributed spaceborne SAR-GMTI system, which includes hybrid along-track and cross-track baseline. When the ground scenes are flat earth, the modified SAR-DPCA and SAR-ATI technique are proposed. When the ground scenes are fluctuant mountainous area, an adaptive SAR-DPCA technique is proposed to settle the problem under some conditions.
In chapter 5, we proposed a robust optimum adaptive clutter suppression, moving targets detection, velocity measurement and target relocation technique for distributed spaceborne multi-baseline SAR-GMTI systems. Firstly, Some realistic problems related to the implementation of the processor are investigated, which include system multiplicative phase noise and steering vector mismatch. The diagonally loading techniques is resorted to improve the estimation of clutter statistics in the presence of multiplicative noise. A prior information, like road network information, is integrated into the optimum adaptive processor to reduce moving target steering vector mismatch. Secondly, two hypotheses and multiple hypotheses CFAR testing technique are proposed, which are based on the prior information of road network. Lastly, based on a priori information, the target velocity measurement and relocation technique are proposed, which improve the estimation accuracy with low computation load.
In chapter 6, we summarize the major work of the thesis, the innovation point and the problems needs to be improved.
引文
[1]魏钟铨等.合成孔径雷达卫星[M].北京:科学出版社, 2001.
[2]袁孝康.星载合成孔径雷达导论[M].北京:国防工业出版社, 2003.
[3] R. M. Goldstein, H. A. Zebker, C. L. Werner. Satellite Radar Interferometry: two-Dimensional Phase Unwrapping[J]. Radio Science, 1988, 23(4):713~720.
[4] H. A. Zebker, et al. Accuracy of Topographic Maps Derived from ERS-1 Interferometric Radar[J]. IEEE Trans. on Geoscience and Remote Sensing, 1994, 32(4) : 823~836.
[5] Riccardo Lanari, et al. Generation of digital elevation models by using SIR-C&X-SAR multifrequency two-pass Interferometry: the Etna case study. IEEE Trans. on Geoscience and Remote Sensing, 1996, 34(5) : 1097-1114.
[6] Yuhsyen Shen, et al. Shuttle Radar Topography Mission (SRTM) Flight System Design and Operations Overview[C]∥Sendai, Japan: Proceedings of SPIE Conference on Microwave Remote Sensing of the Atmosphere and Environment, 2000: 167~178.
[7] A. Moreira, G. Krieger, I. Hajnsek, et al. Single-Pass SAR Interferometry with a Tandem TerraSAR-X Configuration [C]∥Ulm, Germany: EUSAR’04, 2004: 53~54.
[8] Gerhard Krieger, Alberto Moreira, Irena Hajnsek, et al. A Tandem TerraSAR-X Configuration for Single-Pass SAR Interferometry[C]∥RADAR 2004.
[9] Gerhard Krieger, Alberto Moreira, Hauke Fiedler, et al. TanDEM-X: A Satellite Formation for High-Resolution SAR Interferometry[J]. IEEE Trans. on Geoscience and Remote Sensing, 2007, 45(11): 3317~3341.l
[10] Shen Chiu. SAR along-track interferometry with application to RADARSAT-2 ground moving target indication[C]∥Agia Pelagia, GRECE: Proceedings of SPIE Image and Signal Processing for Remote Sensing, 2003: 246~255.
[11] A. Thompson, C. Livingstone. Moving target performance for Radarsta-2[C]∥Proc. IGARSS, Vol.6, Honolulu, HI, 2000: 2599~2601.
[12] Shen Chiu. Performance of Radarsat-2 SAR-GMTI processors at high SAR Resolutions. Defence Research Establishment Ottawa[R]. Technical Report DREO TR 2000-093, Nov. 2000.
[13] Z. Li, Z. Bao, H. Li, et al. Image Auto-Coregistraion and InSAR Interferogram Estimation Using Joint Subspace Projection[J]. IEEE Trans. on Geosci. and Remote Sensing, 2006, 44(2): 288~297.
[14]黄海风.分布式星载SAR干涉测高系统技术研究[D].长沙:国防科技大学电子科学与工程学院, 2005.
[15] D. Massonnet. Capabilities and Limitations of the InterferometricCartwheel[J]. IEEE Trans. on Geoscience and Remote Sensing, 2001, 39(3): 506~520.
[16] F. Martinerie, S. Ramongassie, B. Deligny. Interferometric Cartwheel Payload : Development Status And Current Issues[C].∥Sydney, Australia: Proc. IGARSS’01, 2001: 390~392.
[17] D. Massonnet. The interferometric cartwheel: a constellation of passive satellites to produce radar images to be coherently combined[J]. Int. J. Remote Sensing, 2001, 22(12): 2413~2430.
[18] D. Massonnet, E. Thouvenot, S. Ramongassie. A wheel of passive radar microsats for upgrading existing SAR projects[C]∥Honolulu: IGARSS 2000, 2000: 1000~1003.
[19] H. Fiedler, G. Krieger, F. Jochim, et al. Analysis of Bistatic Configurations for Spaceborne SAR Interferometry[C].∥Proc. EUSAR’02, Cologne, Germany, 2002: 29~32.
[20] G. Krieger, M. Wendler. Comparison of the Interferometric Performance for Spaceborne Parasitic SAR Configurations[C].∥Proc. EUSAR’02. Berlin, 2002: 467~470.
[21] G. Krieger, M. Wendler. Comparison of the Interferometric Performance for Spaceborne Parasitic SAR Configurations[C]∥Berlin: EUSAR 2002, 2002: 467~470.
[22] A. Moreira, G. Krieger, I. Hajnsek ,et al. TanDEM-X: a TerraSAR-X add-on satellite for single-pass SAR interferometry[C]∥Anchorage, Alaska: Proc. of the IEEE IGARSS 2004, 2004: 1000~1003.
[23] G. Krieger, A. Moreira. Tandem-X: mission concept, product definition and performance prediction[C]∥Dresden Germany: EUSAR 2006, 2006.
[24] H. Fiedler, G.. Krieger. The Tandem-X mission design and data acquisition plan[C]∥Dresden Germany: EUSAR 2006, 2006.
[25] Rich Burns, Craig A. McLaughlin, Jesse Leitner, et al, TechSat21: Formation Design, Control and Simulation[C].∥IEEE Aerospace Conference, Big Sky, MT, 2000: 19~25.
[26] A. Moccia, G. Rufino, M. D'Errico, et al. BISSAT: a bistatic SAR for Earth observation[C].∥Toronto, Canada: Proc. IGARSS’02. 2002: 2628~2630.
[27] N. Evans, P. Lee, Ralph Girard. The RADARSAT-2&3 Topographic Mission[C]∥Proc. EUSAR’02, Cologne, Germany, 2002: 37~40.
[28] P. F. Lee, K. James. The RADARSAT-2/3 Topographic Mission[C].∥Sydney, Australian: Proc. IGARSS’01, 2001:499~501.
[29]舒宁,雷达影像干涉测量原理[M].武汉:武汉大学出版社, 2003.
[30]王超,张红,刘智.星载合成孔径雷达干涉测量[M].北京:科学出版社, 2002.
[31] R.Bamler, P.Hartl. Synthetic aperture radar interferometry[J]. Inverse Problem, 1998, 14: R1~R54.
[32] P. Rosen, S. Hensley, I. R. Joughin, et al. Synthetic aperture radar interferometry[J]. Proc. IEEE, 2000, 88(3): 333~382.
[33]孙造宇.星载分布式InSAR信号仿真与处理研究[D].长沙:国防科学技术大学电子科学与工程学院, 2007.
[34] J. S. Lee, K. P. Papathanassiou, T. L. Ainsworth, et al. A new technique for noise filtering of SAR interferometric phase images[J]. IEEE Trans. Geosci. Remote Sensing, 1998, 36(5): 1456~1465.
[35] U. Spagnolini. 2-D phase unwrapping and instantaneous frequency estimation[J]. IEEE Trans. Geosci. Remote Sensing, 1995, 33(3): 579~589.
[36] E. Trouvé, M. Caramma, H. Ma?tre. Fringe detection in noisy complex interferograms[J]. Appl. Opt., 1996, 35(20): 3799~3806.
[37] E. Trouvé, J.M. Nicolas, H. Ma?tre. Improving phase unwrapping techniques by the use of local frequency estimates[J]. IEEE Trans. Geosci. Remote Sensing, 1998, 36(6): 1963~1972.
[38] Gordon W. Davidson, Richard Bamler. Multiresolution phase unwrapping for SAR interferometry[J]. IEEE Trans. Geosci. Remote Sensing, 1999, 37(1): 163~174.
[39]朱岱寅,朱兆达,谢秋成.一种基于局部频率估计的地形自适应干涉图滤波器[J].电子学报, 2002, 30(12): 1853~1856.
[40]李海,李真芳,廖桂生等. InSAR干涉相位图生成的图像配准自补偿方法[J].中国科学(E辑), 2006, 36(2): 191~201.
[41] Hai Li, Zhenfang Li, Guisheng Liao, et al, An estimation method for InSAR interferometric phase combined with image auto-coregistration[J]. Science in China (series F), 2006, 49(5): 632~646.
[42] Carlos López-Martínez, Xavier Fàbregas. Modeling and Reduction of SAR Interferometric Phase Noise in the Wavelet Domain[J]. IEEE Trans. Geosci. Remote Sensing, 2002, 40(12): 2553~2566.
[43]何儒云,王耀南.一种基于小波变换的InSAR干涉图滤波方法[J].测绘学报, 2006, 35(2): 128~131.
[44]岳焕印,郭华东,王长林等. SAR干涉图的静态小波域MAP滤波[J].遥感学报, 2002, 6(6): 456~463.
[45]汪鲁才,王耀南,毛六平.基于小波变换和中值滤波的InSAR干涉图像滤波方法[J].测绘学报, 2005, 34(2): 108~112.
[46]郭春生,朱兆达,朱岱寅.基于PD算子的InSAR干涉图滤波研究[J].南京航空航天大学学报, 2003, 35(1): 72~76
[47]郭春生. InSAR成像算法研究[D].南京:南京航空航天大学信息科学与技术学院, 2002.
[48] D. C. Ghiglia, M. D. Pritt. Two-dimensional phase unwrapping theory, algorithms, and software[M]. New York: John Wiley & Sons, Inc, 1998.
[49] W. Xu, I. Cumming. A region-growing algorithm for InSAR phase unwrapping[J]. IEEE Trans. on Geosci. and Remote Sensing, 1999, 37(1): 124~134.
[50] M. Costantini. A novel phase unwrapping method based on Network programming[J]. IEEE Trans. on Geosci. and Remote Sensing, 1998, 36(3): 813~831.
[51] Wei Xu, Ee Chien Chang, Leong Keong Kwoh, et al. Phase-unwrapping of SAR interferogram with multi-frequency or multi-baseline[C].∥California, USA: Proc. IGARSS’94, 1994: 730~732.
[52] G. Poggi, A. P. R. Ragozini, D. Servadei. A Bayesian Approach for SAR Interferometric Phase Restoration[C].∥Proc. IEEE Int. Geoscience and Remote Sensing Symp’2000, Naples Univ, Italy, 2000: 3202~3205.
[53] Maxim. V. Vinogradov. Phase unwrapping method for the multifrequency and multibaseline interferometry[C].∥Seattle, USA: Proc. IGARSS’98, 1998:1103~1105.
[54] V. Pascazio, G. Schirinzi. Multifrequency InSAR Height Reconstruction Through Maximum Likelihood Estimation of Local Planes Parameters[J]. IEEE Trans. On Image Processing, 2002, 11(12): 1478~1489.
[55] U Soergel, K Strulz, U Thoenessen. Enhancement of interferometric SAR data using segmented intensity information in urban areas[C].∥Honolulu, HI: Proc. IGARSS, 2000: 3216~3218.
[56] Henri Ma?tre.合成孔径雷达图像处理[M].孙洪等译,北京:电子工业出版社, 2005.
[57]陈绍武,王卫星,金文标.基于边缘特征和模糊理论的阴影检测[J].微计算机信息, 2007, 23(1-3): 294~296.
[58]王健,向茂生,李邵恩.一种基于InSAR相干系数的SAR阴影提取方法[J].武汉大学学报, 2005, 30(12): 1063~1066.
[59] A.J. Wilkinson. Synthetic aperture radar interferometry a model for the joint statistics in Layover areas[C].∥Capetown, SA: Proc. COMSIG’98, 1998: 333~338.
[60] F. Gatelli, A. Monti Guarnieri. The wavenumber shift in SAR interferometry[J]. IEEE Trans. Geosci. Remote Sensing, 1994, 32(4): 855~865.
[61] F. Gini, F. Lombardini, P. Matteucci, et al. System and estimation problems for multibaseline InSAR imaging of multiple layovered reflectors[C]∥Sydney, Australia: Proc. IEEE Int. Geosci. Remote Sensing Symp, 2001: 115~117.
[62] F. Gini, F. Lombardini. Multilook APES for multibaseline SAR interferometry[J]. IEEE Trans. Signal Processing, 2002, 50(7): 1800~1803.
[63] F. Lombardini, F. Gini, P. Matteucci. Application of array processingtechniques to multibaseline InSAR for layover solution[C]∥Atlanta, GA: Proc. IEEE Radar Conf., 2001: 210~215.
[64] F. Gini, F. Lombardini, M.. Montanari. Layover solution in multibaseline SAR interferometry[J]. IEEE Trans on Aerospace and Electronic Systems, 2002, 38(4): 1344~1356 .
[65] F. Bordoni, F. Gini, L. Verrazzani. Capon-LS for model order selection of multicomponent interferometric SAR signals[J]. IEE Proc. Radar Sonar Navig., 2004, 151(5): 299~305.
[66] F. Lombardini, F. Gini. Model Order Selection in Multi-baseline Interferometric Radar Systems[J]. EURASIP Journal on Applied Signal Processing, 2005, 20: 3206~3219.
[67] F. Lombardini, M. Montanari, F. Gini. Reflectivity estimation for multibaseline interferometric radar imaging of multiple extended sources[J]. IEEE Trans. Signal Process., 2003, 51(6): 1508-1519.
[68] Fulvio Gini, Federica Bordoni. On the behavior of information theoretic criteria for model order selection of InSAR signals corrupted by multiplicative noise[J]. Signal Processing, 2003, 83(5): 1047~1063.
[69] Jiao Guo, Zhenfang Li and Zheng Bao. Using Multibaseline InSAR to Recover Layovered Terrain Considering Wideband Array Problem[J]. IEEE Geosci. Remote Sens. Letters, 2008, 5(4):583~587.
[70] Michael Eineder and Nico Adam. A maximum-likelihood estimator to simultaneously unwrap, geocode, and fuse SAR interferograms from different viewing geometries into one digital elevation model[J]. IEEE Trans. Geosci. Remote Sensing, 2005, 43(1):24~36.
[71] Michael Eineder, and Steffen Suchandt, Recovering Radar Shadow to Improve Interferometric Phase Unwrapping and DEM Reconstruction, IEEE Trans. on Geosci. and Remote Sensing, 2003, 41(12):2959-2962.
[72] Eugenio Sansosti, A Simple and Exact Solution for the Interferometic and Stereo SAR Geolocation Problem[J]. IEEE Trans. Geosci. Remote Sensing, 2004, 15(8): 1625~1634.
[73] Gerhard Krieger, Hauke Fiedler, Irena Hajnsek, et al. TanDEM-X: Mission Conceptand Performance Analysis[C]∥Seoul, Korea: IEEE International Geoscience and Remote Sensing Symposium, 2005: 4890~4893.
[74] Manfred Zink, Gerhard Krieger, Hauke Fiedler, et al.The TanDEM-X Mission: Overview and Status[C]∥Barcelona, Spain: IGARSS’07, 2007.
[75] Hauke Fiedler, Gerhard Krieger, Manfred Zink, et al. The TanDEM-X Mission: An Overview[C]∥Adelaide, Australia: International Radar Conference, 2008.
[76] Aguttes J P. The SAR Train concept: required antenna area distributed over Nsmaller satellites, increase of performance by N[C].∥Toronto, Canada:Proc. of the IEEE IGARSS, 2003:542~544.
[77] Beaulne P D, Gierull C H, Livinstone C E, et al. Preliminary design of a SAR-GMTI processing system for Radarsat-2 MODEX data. Proc. of the IEEE IGARSS 2003, July 2003: 1019-1021
[78] Vant M, Livingstone C, Rey M, et al. Canadian experience on Radarsat-1 and Radarsat-2 GMTI for surveillance. AIAA/ICAS International Air and Space Symposium and Exposition: The Next 100 Year. July 2003, Dayton Ohio, AIAA 2003-2820
[79] http://www.radarsat2.info
[80] Lombardo P, Pastina D, Colone F, et al. Potentialities of a multichannel radar obtained by splitting the antenna of the COSMO-SkyMed SAR into multiple sub-apertures. EUSAR Proc. Ulm, Germany, 2004: 35-38
[81] Verdone G R, Viggiano R, Lopinto E, et al. Processing algorithms for COSMO-SkyMed SAR sensor. Proc. of the IEEE IGARSS 2002, June 2002,: 2771-2774
[82] Liu Congfeng, Liao Guisheng and Zeng Cao. Canonical Framework for ATI and DPCA[C]. Shanghai, China:International Conference on wireless Communications, Networking and Mobile Computing, 2007:714~717.
[83]禹卫东,李世强.装备预先研究项目验收技术总结报告[R].北京:中国科学院电子学研究所,2007.
[84]曾斌.分布式卫星SAR慢动目标检测及关键技术研究[D].成都:电子科技大学, 2006.
[85]行坤.合成孔径雷达动目标检测与定位方法研究[D].西安:西安电子科技大学, 2006.
[86] Shen Chiu and C. Livingstone. A comparison of displaced phase centre antenna and along-track interferometry techniques for RADARSAT-2 ground moving target indication[J]. Can. J. Remote Sensing, 2005, 31(1):3~51.
[87] C. Livingstone, I. Sikaneta, C.H. Gierull, et al, An Airborne Synthetic Aperture Radar (SAR) experiment to support RADARSAT-2 Ground Moving Target Indication (GMTI)[J]. Canadian Journal of Remote Sensing, 2002, 28(6):794~813.
[88] C. Livingstone and A. Thompson. The Moving Object detection experiment on RADARSAT-2[J]. Canadian Journal of Remote Sensing, 2004, 30(3):355~368.
[89]孟祥东,王彤,保铮.双星编队SAR-GMTI中垂直基线对杂波抑制性能的影响[C].北京:星载SAR/GMTI技术研讨论文集(秘密),2007:41~51.
[90] D. Massonnet, The interferometric cartwheel: A constellation of passive satellites to produce radar images to be coherently combined[J]. Int. J. Remote Sens.,2001,22(12):2413~2430.
[91]杨凤凤.星载雷达GMTI系统与信号处理研究[D].长沙:国防科学技术大学博士学位论文,2007.
[92] Lei Yang, Tong Wang, and Zheng Bao. Ground Moving Target Indication Using an InSAR System With a Hybrid Baseline[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2008,5(3):373~377.
[93]黄波.主星带伴随小卫星SAR系统ATI慢动目标测速精度研究[D].成都:电子科技大学, 2007.
[94]秦放.分布式卫星系统动目标检测及混合基线相位分离方法研究[D].成都:电子科技大学, 2007.
[95]赵鸿冰.机载合成孔径雷达运动目标检测方法研究[D].成都:电子科技大学, 2007.
[96] C. H. Gierull. Statistical analysis of multilook SAR interferograms for CFAR detection of ground moving targets[J]. IEEE Trans. Geosci. Remote Sensing, 2004,42(4):691~701.
[97] S. Chiu. A constant false alarm rate (CFAR) detector for RADARSAT-2 along-track interferometry[J]. Canadian Journal of Remote Sensing, 2005, 31(1):73~84.
[98]时公涛,高贵,蒋咏梅等.基于干涉图的双通道合成孔径雷达地面运动目标检测新方法[J].自然科学进展,2008,18(5):559~572.
[99]袁昊,周荫清,李景文.基于幅度和相位联合的ATI动目标检测新方法[J].北京航空航天大学学报, 2007, 33(2): 169~175.
[100] F. Meyer, S. Hinz, Rupert Müller, et al. Towards Traffic Monitoring with TerraSAR-X[J]. Can. J. Remote Sensing, 2007, 33(1):39~51.
[101] Franz Meyer, Stefan Hinz, Andreas Laika, et al. Performance analysis of the TerraSAR-X traffic monitoring concept[J]. ISPRS Journal of Photogrammetry & Remote Sensing, 2004, 61(3-4):225~242.
[102]刘颖,廖桂生,周争光.对图像配准误差稳健的分布式星载SAR地面运动目标检测及高精度的测速定位方法[J].电子学报,2007, 35(6):1009~1014.
[103] Zhenfang Li, Zheng Bao, Fengfeng Yang. Ground moving target detection and location based on SAR images for distributed spaceborne SAR[J]. Science in China (Series F), 2005,48(5):632~646.
[104]李真芳.分布式小卫星SAR-InSAR-GMTI的处理方法[D].西安:西安电子科技大学博士学位论文,2006.
[105] G.Franceschetti, M.Migliaccio, D.Riccio, et al. SARS: A Synthetic Aperture Radar (SAR) Raw Signal Simulator[J]. IEEE Trans. Geosci. Remote Sensing, 1992,30(1):110~123.
[106]王敏.天基分布式SAR系统多任务仿真研究[D].长沙:国防科学技术大学博士学位论文,2007.
[107] M.Eineder. Efficient simulation of SAR interferogram of large areas and of rugged terrain[J]. IEEE Trans. Geosci. Remote Sensing, 2003,41(6):1415~1427.
[108]王青松.天基InSAR理想干涉量的仿真与应用研究[D].长沙:国防科学技术大学硕士学位论文,2008.
[109]路兴强,天基分布式InSAR系统建模与仿真研究,国防科技大学博士学位论文,2006.10.
[110] M. Eineder. Problems and Solutions for INSAR Digital Elevation Model Generation of Mountainous Terrain[C].∥ITALY:Proc. FRINGE 2003 Workshop, 2003:1~5.
[111] Bin Cai, Diannong Liang and Zhen Dong. A New Adaptive Multiresolution Noise-Filtering Approach for SAR Interferometric Phase Images[J]. IEEE Geosci. Remote Sens. Letters, 2008,5(2):266~270.
[112] F. Lombardini, J. Ender, L. R??ing, et al. Experiments of Interferometric Layover Solution with the Three-antenna Airborne AER-II SAR System[C].∥Anchorage, Alaska:IGARSS, 2004:3341~3344.
[113] S. M.凯依.现代谱估计原理与应用[M].北京:科学出版社, 1994.
[114]张贤达.现代信号处理(第二版)[M].北京:清华大学出版社, 2002.
[115]王永良,陈辉,彭应宁等.空间谱估计理论与算法[M].北京:清华大学出版社, 2004.
[116]张贤达,保铮.通信信号处理[M].北京:国防工业出版社, 2000.
[117] Jian Li and Petre Stoica. Efficient Mixec-Spectrum Estimation with Applications to Target Feature Extraction[J]. IEEE Trans. Signla Processing, 1996, 44(2): 281~295.
[118] Tong, Wang, Zheng Bao, Zhang Zhen hua, et al. Improving Coherence of Complex Image Pairs Obtained by Along-track Bistatic SARs Using Range-azimuth Prefiltering[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008,46(1):3~13.
[119]王彤,保铮.提高沿航向干涉法性能的最小二乘图像对补偿方法[J].自然科学进展, 2008, 18(12):1484~1490.
[120]王彤,保铮.提高星载SAR-GMTI杂波抑制性能的一种图像均衡方法[C].∥北京:星载SAR/GMTI技术研讨论文集(秘密),2007:25~61.
[121] C.H.Gierull. Digital channel balancing of along-track interferometric SAR data[R]. Defence Research Establishment Ottawa:Technical Memorandum TM 2003-024,2003.
[122] S. Chiu. A Simulation Study of Multi-Channel RADARSAT-2 GMTI[R]. Canada Ottawa: Defence R&D, 2006.
[123] S. Chiu, C.H.Gierull. Multi-channel receiver concepts for radarsar-2 ground moving target indication[C]∥Dresden, Germany: Proceedings of EUSAR’06, 2006.
[124] Richard Klemm. Principles of space-time adaptive processing[M]. London, UK: The institution of Electrical Engineers, 2002.
[125] Soumekh M. Synthetic aperture radar signal processing with MATLAB algorithms[M]. New York: Wiley, 1999: 575~586.
[126] Soumekh M. Moving target detection and imaging using an X band along-track monopulse SAR[J]. Trans. AES, 2002, 38(1): 315~333.
[127]张永胜.星载分布式InSAR概念系统结构与误差研究[D].国防科学技术大学博士学位论文,2007.
[128] Zhang Yong-sheng, Liang Dian-nong, Dong Zhen. Analysis of time and frequency synchronization errors in spaceborne parasitic interferometric SAR system[C]∥Denver, USA: Proc. of the IEEE IGARSS’06, 2006: 3047 - 3050.
[129] Matthias Wei. Time and frequency synchronization aspects for bistatic SAR systems[C]∥Ulm, Germany: EUSAR, 2004: 395~398.
[130] M. Eineder. Oscillator clock drift compensation in bistatic interferometric SAR[C]∥Toulouse, France: IGARSS’03, 2003.
[131] C. H. Gierull, I. C. Sikaneta. Estimating the Effective Number of Looks in Interferometric SAR Data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(8): 1733~1742.
[132] Shen Chiu. SAR along-track interferometry with application to RADARSAT-2 ground moving target indication[C]∥Agia Pelagia: Proceedings of SPIE, Vol. 4885, 2003: 246~255.
[133]周宗潭,董国华,徐昕等.独立成份分析[M].北京:电子工业出版社, 2007.
[134]高贵. SAR图像目标ROI自动获取技术研究[D].长沙:国防科学技术大学电子科学与工程学院, 2007.
[135]罗鹏飞,张文明,刘忠等.统计信号处理基础-估计与检测理论[M].北京:电子工业出版社, 2006.
[136]何友,王国宏,彭应宁等.多传感器信息融合及应用[M].北京:电子工业出版社, 2000.
[137]穆冬.干涉合成孔径雷达成像技术研究[D].南京:南京航空航天大学, 2001.
[138]索志勇,李真芳,保铮等.混合基线InSAR构形下SAR-GMTI方法研究[J].中国科学E辑, 2009, 39(1):1~8.
[139]李真芳,保铮,杨凤凤.基于成像的分布式卫星SAR系统地面运动目标检测(GMTI)及定位技术[J].中国科学E辑:信息科学,2005,35(6):597~609.
[140]吴洪.非均匀杂波环境下相控阵机载雷达STAP技术研究[D].长沙:国防科学技术大学电子科学与工程学院, 2007.
[141] Wiks M C, Rangaswamy M, Adve R., et al. Space-time adaptive processing (A knowledge-based perspective for airborne radar)[J]. IEEE Signal Processing Magazine, 2006: 51~65.
[142] Capraro G T, Farina A, Grifiths H., et al. Knowledge-based radar signal and data processing[J]. IEEE Signal Processing Magazine, 2006:18~29.
[143] Guerci J R, Baranoski E J. Knowledge-aided adaptive radar at DARPA[J]. IEEE Signal Processing Magazine, 2006:41~50.
[144]王永良,彭应宁.空时自适应信号处理[M].北京:清华大学出版社, 2000.
[145] R. Klemm. Space-Time Adaptive Processing: Principles and Applications [M]. London: Proc. IEE Radar-Sonar-Navigation and Avionics, 1998.
[146] Christ D. Richmond. Performance of the Adaptive Sidelobe Blanker Detection Algorithm in Homogeneous Environments[J]. IEEE Trans. Signal Processing, 2000,48(5): 1235~1247.
[147] N. B. Pulsone and C. M. Rader. Adaptive Beamformer Orthogonal Rejection Test[J]. IEEE Trans. Signal Processing, 2001,49(3):521~529.
[148] H. Cox, R. M. Zeskind, and M. H. Owen. Robust adaptive beamforming[J]. IEEE Trans. Acoust., Speech, Signal Processing,1987,35(10):1365~1376.
[2]袁孝康.星载合成孔径雷达导论[M].北京:国防工业出版社, 2003.
[3] R. M. Goldstein, H. A. Zebker, C. L. Werner. Satellite Radar Interferometry: two-Dimensional Phase Unwrapping[J]. Radio Science, 1988, 23(4):713~720.
[4] H. A. Zebker, et al. Accuracy of Topographic Maps Derived from ERS-1 Interferometric Radar[J]. IEEE Trans. on Geoscience and Remote Sensing, 1994, 32(4) : 823~836.
[5] Riccardo Lanari, et al. Generation of digital elevation models by using SIR-C&X-SAR multifrequency two-pass Interferometry: the Etna case study. IEEE Trans. on Geoscience and Remote Sensing, 1996, 34(5) : 1097-1114.
[6] Yuhsyen Shen, et al. Shuttle Radar Topography Mission (SRTM) Flight System Design and Operations Overview[C]∥Sendai, Japan: Proceedings of SPIE Conference on Microwave Remote Sensing of the Atmosphere and Environment, 2000: 167~178.
[7] A. Moreira, G. Krieger, I. Hajnsek, et al. Single-Pass SAR Interferometry with a Tandem TerraSAR-X Configuration [C]∥Ulm, Germany: EUSAR’04, 2004: 53~54.
[8] Gerhard Krieger, Alberto Moreira, Irena Hajnsek, et al. A Tandem TerraSAR-X Configuration for Single-Pass SAR Interferometry[C]∥RADAR 2004.
[9] Gerhard Krieger, Alberto Moreira, Hauke Fiedler, et al. TanDEM-X: A Satellite Formation for High-Resolution SAR Interferometry[J]. IEEE Trans. on Geoscience and Remote Sensing, 2007, 45(11): 3317~3341.l
[10] Shen Chiu. SAR along-track interferometry with application to RADARSAT-2 ground moving target indication[C]∥Agia Pelagia, GRECE: Proceedings of SPIE Image and Signal Processing for Remote Sensing, 2003: 246~255.
[11] A. Thompson, C. Livingstone. Moving target performance for Radarsta-2[C]∥Proc. IGARSS, Vol.6, Honolulu, HI, 2000: 2599~2601.
[12] Shen Chiu. Performance of Radarsat-2 SAR-GMTI processors at high SAR Resolutions. Defence Research Establishment Ottawa[R]. Technical Report DREO TR 2000-093, Nov. 2000.
[13] Z. Li, Z. Bao, H. Li, et al. Image Auto-Coregistraion and InSAR Interferogram Estimation Using Joint Subspace Projection[J]. IEEE Trans. on Geosci. and Remote Sensing, 2006, 44(2): 288~297.
[14]黄海风.分布式星载SAR干涉测高系统技术研究[D].长沙:国防科技大学电子科学与工程学院, 2005.
[15] D. Massonnet. Capabilities and Limitations of the InterferometricCartwheel[J]. IEEE Trans. on Geoscience and Remote Sensing, 2001, 39(3): 506~520.
[16] F. Martinerie, S. Ramongassie, B. Deligny. Interferometric Cartwheel Payload : Development Status And Current Issues[C].∥Sydney, Australia: Proc. IGARSS’01, 2001: 390~392.
[17] D. Massonnet. The interferometric cartwheel: a constellation of passive satellites to produce radar images to be coherently combined[J]. Int. J. Remote Sensing, 2001, 22(12): 2413~2430.
[18] D. Massonnet, E. Thouvenot, S. Ramongassie. A wheel of passive radar microsats for upgrading existing SAR projects[C]∥Honolulu: IGARSS 2000, 2000: 1000~1003.
[19] H. Fiedler, G. Krieger, F. Jochim, et al. Analysis of Bistatic Configurations for Spaceborne SAR Interferometry[C].∥Proc. EUSAR’02, Cologne, Germany, 2002: 29~32.
[20] G. Krieger, M. Wendler. Comparison of the Interferometric Performance for Spaceborne Parasitic SAR Configurations[C].∥Proc. EUSAR’02. Berlin, 2002: 467~470.
[21] G. Krieger, M. Wendler. Comparison of the Interferometric Performance for Spaceborne Parasitic SAR Configurations[C]∥Berlin: EUSAR 2002, 2002: 467~470.
[22] A. Moreira, G. Krieger, I. Hajnsek ,et al. TanDEM-X: a TerraSAR-X add-on satellite for single-pass SAR interferometry[C]∥Anchorage, Alaska: Proc. of the IEEE IGARSS 2004, 2004: 1000~1003.
[23] G. Krieger, A. Moreira. Tandem-X: mission concept, product definition and performance prediction[C]∥Dresden Germany: EUSAR 2006, 2006.
[24] H. Fiedler, G.. Krieger. The Tandem-X mission design and data acquisition plan[C]∥Dresden Germany: EUSAR 2006, 2006.
[25] Rich Burns, Craig A. McLaughlin, Jesse Leitner, et al, TechSat21: Formation Design, Control and Simulation[C].∥IEEE Aerospace Conference, Big Sky, MT, 2000: 19~25.
[26] A. Moccia, G. Rufino, M. D'Errico, et al. BISSAT: a bistatic SAR for Earth observation[C].∥Toronto, Canada: Proc. IGARSS’02. 2002: 2628~2630.
[27] N. Evans, P. Lee, Ralph Girard. The RADARSAT-2&3 Topographic Mission[C]∥Proc. EUSAR’02, Cologne, Germany, 2002: 37~40.
[28] P. F. Lee, K. James. The RADARSAT-2/3 Topographic Mission[C].∥Sydney, Australian: Proc. IGARSS’01, 2001:499~501.
[29]舒宁,雷达影像干涉测量原理[M].武汉:武汉大学出版社, 2003.
[30]王超,张红,刘智.星载合成孔径雷达干涉测量[M].北京:科学出版社, 2002.
[31] R.Bamler, P.Hartl. Synthetic aperture radar interferometry[J]. Inverse Problem, 1998, 14: R1~R54.
[32] P. Rosen, S. Hensley, I. R. Joughin, et al. Synthetic aperture radar interferometry[J]. Proc. IEEE, 2000, 88(3): 333~382.
[33]孙造宇.星载分布式InSAR信号仿真与处理研究[D].长沙:国防科学技术大学电子科学与工程学院, 2007.
[34] J. S. Lee, K. P. Papathanassiou, T. L. Ainsworth, et al. A new technique for noise filtering of SAR interferometric phase images[J]. IEEE Trans. Geosci. Remote Sensing, 1998, 36(5): 1456~1465.
[35] U. Spagnolini. 2-D phase unwrapping and instantaneous frequency estimation[J]. IEEE Trans. Geosci. Remote Sensing, 1995, 33(3): 579~589.
[36] E. Trouvé, M. Caramma, H. Ma?tre. Fringe detection in noisy complex interferograms[J]. Appl. Opt., 1996, 35(20): 3799~3806.
[37] E. Trouvé, J.M. Nicolas, H. Ma?tre. Improving phase unwrapping techniques by the use of local frequency estimates[J]. IEEE Trans. Geosci. Remote Sensing, 1998, 36(6): 1963~1972.
[38] Gordon W. Davidson, Richard Bamler. Multiresolution phase unwrapping for SAR interferometry[J]. IEEE Trans. Geosci. Remote Sensing, 1999, 37(1): 163~174.
[39]朱岱寅,朱兆达,谢秋成.一种基于局部频率估计的地形自适应干涉图滤波器[J].电子学报, 2002, 30(12): 1853~1856.
[40]李海,李真芳,廖桂生等. InSAR干涉相位图生成的图像配准自补偿方法[J].中国科学(E辑), 2006, 36(2): 191~201.
[41] Hai Li, Zhenfang Li, Guisheng Liao, et al, An estimation method for InSAR interferometric phase combined with image auto-coregistration[J]. Science in China (series F), 2006, 49(5): 632~646.
[42] Carlos López-Martínez, Xavier Fàbregas. Modeling and Reduction of SAR Interferometric Phase Noise in the Wavelet Domain[J]. IEEE Trans. Geosci. Remote Sensing, 2002, 40(12): 2553~2566.
[43]何儒云,王耀南.一种基于小波变换的InSAR干涉图滤波方法[J].测绘学报, 2006, 35(2): 128~131.
[44]岳焕印,郭华东,王长林等. SAR干涉图的静态小波域MAP滤波[J].遥感学报, 2002, 6(6): 456~463.
[45]汪鲁才,王耀南,毛六平.基于小波变换和中值滤波的InSAR干涉图像滤波方法[J].测绘学报, 2005, 34(2): 108~112.
[46]郭春生,朱兆达,朱岱寅.基于PD算子的InSAR干涉图滤波研究[J].南京航空航天大学学报, 2003, 35(1): 72~76
[47]郭春生. InSAR成像算法研究[D].南京:南京航空航天大学信息科学与技术学院, 2002.
[48] D. C. Ghiglia, M. D. Pritt. Two-dimensional phase unwrapping theory, algorithms, and software[M]. New York: John Wiley & Sons, Inc, 1998.
[49] W. Xu, I. Cumming. A region-growing algorithm for InSAR phase unwrapping[J]. IEEE Trans. on Geosci. and Remote Sensing, 1999, 37(1): 124~134.
[50] M. Costantini. A novel phase unwrapping method based on Network programming[J]. IEEE Trans. on Geosci. and Remote Sensing, 1998, 36(3): 813~831.
[51] Wei Xu, Ee Chien Chang, Leong Keong Kwoh, et al. Phase-unwrapping of SAR interferogram with multi-frequency or multi-baseline[C].∥California, USA: Proc. IGARSS’94, 1994: 730~732.
[52] G. Poggi, A. P. R. Ragozini, D. Servadei. A Bayesian Approach for SAR Interferometric Phase Restoration[C].∥Proc. IEEE Int. Geoscience and Remote Sensing Symp’2000, Naples Univ, Italy, 2000: 3202~3205.
[53] Maxim. V. Vinogradov. Phase unwrapping method for the multifrequency and multibaseline interferometry[C].∥Seattle, USA: Proc. IGARSS’98, 1998:1103~1105.
[54] V. Pascazio, G. Schirinzi. Multifrequency InSAR Height Reconstruction Through Maximum Likelihood Estimation of Local Planes Parameters[J]. IEEE Trans. On Image Processing, 2002, 11(12): 1478~1489.
[55] U Soergel, K Strulz, U Thoenessen. Enhancement of interferometric SAR data using segmented intensity information in urban areas[C].∥Honolulu, HI: Proc. IGARSS, 2000: 3216~3218.
[56] Henri Ma?tre.合成孔径雷达图像处理[M].孙洪等译,北京:电子工业出版社, 2005.
[57]陈绍武,王卫星,金文标.基于边缘特征和模糊理论的阴影检测[J].微计算机信息, 2007, 23(1-3): 294~296.
[58]王健,向茂生,李邵恩.一种基于InSAR相干系数的SAR阴影提取方法[J].武汉大学学报, 2005, 30(12): 1063~1066.
[59] A.J. Wilkinson. Synthetic aperture radar interferometry a model for the joint statistics in Layover areas[C].∥Capetown, SA: Proc. COMSIG’98, 1998: 333~338.
[60] F. Gatelli, A. Monti Guarnieri. The wavenumber shift in SAR interferometry[J]. IEEE Trans. Geosci. Remote Sensing, 1994, 32(4): 855~865.
[61] F. Gini, F. Lombardini, P. Matteucci, et al. System and estimation problems for multibaseline InSAR imaging of multiple layovered reflectors[C]∥Sydney, Australia: Proc. IEEE Int. Geosci. Remote Sensing Symp, 2001: 115~117.
[62] F. Gini, F. Lombardini. Multilook APES for multibaseline SAR interferometry[J]. IEEE Trans. Signal Processing, 2002, 50(7): 1800~1803.
[63] F. Lombardini, F. Gini, P. Matteucci. Application of array processingtechniques to multibaseline InSAR for layover solution[C]∥Atlanta, GA: Proc. IEEE Radar Conf., 2001: 210~215.
[64] F. Gini, F. Lombardini, M.. Montanari. Layover solution in multibaseline SAR interferometry[J]. IEEE Trans on Aerospace and Electronic Systems, 2002, 38(4): 1344~1356 .
[65] F. Bordoni, F. Gini, L. Verrazzani. Capon-LS for model order selection of multicomponent interferometric SAR signals[J]. IEE Proc. Radar Sonar Navig., 2004, 151(5): 299~305.
[66] F. Lombardini, F. Gini. Model Order Selection in Multi-baseline Interferometric Radar Systems[J]. EURASIP Journal on Applied Signal Processing, 2005, 20: 3206~3219.
[67] F. Lombardini, M. Montanari, F. Gini. Reflectivity estimation for multibaseline interferometric radar imaging of multiple extended sources[J]. IEEE Trans. Signal Process., 2003, 51(6): 1508-1519.
[68] Fulvio Gini, Federica Bordoni. On the behavior of information theoretic criteria for model order selection of InSAR signals corrupted by multiplicative noise[J]. Signal Processing, 2003, 83(5): 1047~1063.
[69] Jiao Guo, Zhenfang Li and Zheng Bao. Using Multibaseline InSAR to Recover Layovered Terrain Considering Wideband Array Problem[J]. IEEE Geosci. Remote Sens. Letters, 2008, 5(4):583~587.
[70] Michael Eineder and Nico Adam. A maximum-likelihood estimator to simultaneously unwrap, geocode, and fuse SAR interferograms from different viewing geometries into one digital elevation model[J]. IEEE Trans. Geosci. Remote Sensing, 2005, 43(1):24~36.
[71] Michael Eineder, and Steffen Suchandt, Recovering Radar Shadow to Improve Interferometric Phase Unwrapping and DEM Reconstruction, IEEE Trans. on Geosci. and Remote Sensing, 2003, 41(12):2959-2962.
[72] Eugenio Sansosti, A Simple and Exact Solution for the Interferometic and Stereo SAR Geolocation Problem[J]. IEEE Trans. Geosci. Remote Sensing, 2004, 15(8): 1625~1634.
[73] Gerhard Krieger, Hauke Fiedler, Irena Hajnsek, et al. TanDEM-X: Mission Conceptand Performance Analysis[C]∥Seoul, Korea: IEEE International Geoscience and Remote Sensing Symposium, 2005: 4890~4893.
[74] Manfred Zink, Gerhard Krieger, Hauke Fiedler, et al.The TanDEM-X Mission: Overview and Status[C]∥Barcelona, Spain: IGARSS’07, 2007.
[75] Hauke Fiedler, Gerhard Krieger, Manfred Zink, et al. The TanDEM-X Mission: An Overview[C]∥Adelaide, Australia: International Radar Conference, 2008.
[76] Aguttes J P. The SAR Train concept: required antenna area distributed over Nsmaller satellites, increase of performance by N[C].∥Toronto, Canada:Proc. of the IEEE IGARSS, 2003:542~544.
[77] Beaulne P D, Gierull C H, Livinstone C E, et al. Preliminary design of a SAR-GMTI processing system for Radarsat-2 MODEX data. Proc. of the IEEE IGARSS 2003, July 2003: 1019-1021
[78] Vant M, Livingstone C, Rey M, et al. Canadian experience on Radarsat-1 and Radarsat-2 GMTI for surveillance. AIAA/ICAS International Air and Space Symposium and Exposition: The Next 100 Year. July 2003, Dayton Ohio, AIAA 2003-2820
[79] http://www.radarsat2.info
[80] Lombardo P, Pastina D, Colone F, et al. Potentialities of a multichannel radar obtained by splitting the antenna of the COSMO-SkyMed SAR into multiple sub-apertures. EUSAR Proc. Ulm, Germany, 2004: 35-38
[81] Verdone G R, Viggiano R, Lopinto E, et al. Processing algorithms for COSMO-SkyMed SAR sensor. Proc. of the IEEE IGARSS 2002, June 2002,: 2771-2774
[82] Liu Congfeng, Liao Guisheng and Zeng Cao. Canonical Framework for ATI and DPCA[C]. Shanghai, China:International Conference on wireless Communications, Networking and Mobile Computing, 2007:714~717.
[83]禹卫东,李世强.装备预先研究项目验收技术总结报告[R].北京:中国科学院电子学研究所,2007.
[84]曾斌.分布式卫星SAR慢动目标检测及关键技术研究[D].成都:电子科技大学, 2006.
[85]行坤.合成孔径雷达动目标检测与定位方法研究[D].西安:西安电子科技大学, 2006.
[86] Shen Chiu and C. Livingstone. A comparison of displaced phase centre antenna and along-track interferometry techniques for RADARSAT-2 ground moving target indication[J]. Can. J. Remote Sensing, 2005, 31(1):3~51.
[87] C. Livingstone, I. Sikaneta, C.H. Gierull, et al, An Airborne Synthetic Aperture Radar (SAR) experiment to support RADARSAT-2 Ground Moving Target Indication (GMTI)[J]. Canadian Journal of Remote Sensing, 2002, 28(6):794~813.
[88] C. Livingstone and A. Thompson. The Moving Object detection experiment on RADARSAT-2[J]. Canadian Journal of Remote Sensing, 2004, 30(3):355~368.
[89]孟祥东,王彤,保铮.双星编队SAR-GMTI中垂直基线对杂波抑制性能的影响[C].北京:星载SAR/GMTI技术研讨论文集(秘密),2007:41~51.
[90] D. Massonnet, The interferometric cartwheel: A constellation of passive satellites to produce radar images to be coherently combined[J]. Int. J. Remote Sens.,2001,22(12):2413~2430.
[91]杨凤凤.星载雷达GMTI系统与信号处理研究[D].长沙:国防科学技术大学博士学位论文,2007.
[92] Lei Yang, Tong Wang, and Zheng Bao. Ground Moving Target Indication Using an InSAR System With a Hybrid Baseline[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2008,5(3):373~377.
[93]黄波.主星带伴随小卫星SAR系统ATI慢动目标测速精度研究[D].成都:电子科技大学, 2007.
[94]秦放.分布式卫星系统动目标检测及混合基线相位分离方法研究[D].成都:电子科技大学, 2007.
[95]赵鸿冰.机载合成孔径雷达运动目标检测方法研究[D].成都:电子科技大学, 2007.
[96] C. H. Gierull. Statistical analysis of multilook SAR interferograms for CFAR detection of ground moving targets[J]. IEEE Trans. Geosci. Remote Sensing, 2004,42(4):691~701.
[97] S. Chiu. A constant false alarm rate (CFAR) detector for RADARSAT-2 along-track interferometry[J]. Canadian Journal of Remote Sensing, 2005, 31(1):73~84.
[98]时公涛,高贵,蒋咏梅等.基于干涉图的双通道合成孔径雷达地面运动目标检测新方法[J].自然科学进展,2008,18(5):559~572.
[99]袁昊,周荫清,李景文.基于幅度和相位联合的ATI动目标检测新方法[J].北京航空航天大学学报, 2007, 33(2): 169~175.
[100] F. Meyer, S. Hinz, Rupert Müller, et al. Towards Traffic Monitoring with TerraSAR-X[J]. Can. J. Remote Sensing, 2007, 33(1):39~51.
[101] Franz Meyer, Stefan Hinz, Andreas Laika, et al. Performance analysis of the TerraSAR-X traffic monitoring concept[J]. ISPRS Journal of Photogrammetry & Remote Sensing, 2004, 61(3-4):225~242.
[102]刘颖,廖桂生,周争光.对图像配准误差稳健的分布式星载SAR地面运动目标检测及高精度的测速定位方法[J].电子学报,2007, 35(6):1009~1014.
[103] Zhenfang Li, Zheng Bao, Fengfeng Yang. Ground moving target detection and location based on SAR images for distributed spaceborne SAR[J]. Science in China (Series F), 2005,48(5):632~646.
[104]李真芳.分布式小卫星SAR-InSAR-GMTI的处理方法[D].西安:西安电子科技大学博士学位论文,2006.
[105] G.Franceschetti, M.Migliaccio, D.Riccio, et al. SARS: A Synthetic Aperture Radar (SAR) Raw Signal Simulator[J]. IEEE Trans. Geosci. Remote Sensing, 1992,30(1):110~123.
[106]王敏.天基分布式SAR系统多任务仿真研究[D].长沙:国防科学技术大学博士学位论文,2007.
[107] M.Eineder. Efficient simulation of SAR interferogram of large areas and of rugged terrain[J]. IEEE Trans. Geosci. Remote Sensing, 2003,41(6):1415~1427.
[108]王青松.天基InSAR理想干涉量的仿真与应用研究[D].长沙:国防科学技术大学硕士学位论文,2008.
[109]路兴强,天基分布式InSAR系统建模与仿真研究,国防科技大学博士学位论文,2006.10.
[110] M. Eineder. Problems and Solutions for INSAR Digital Elevation Model Generation of Mountainous Terrain[C].∥ITALY:Proc. FRINGE 2003 Workshop, 2003:1~5.
[111] Bin Cai, Diannong Liang and Zhen Dong. A New Adaptive Multiresolution Noise-Filtering Approach for SAR Interferometric Phase Images[J]. IEEE Geosci. Remote Sens. Letters, 2008,5(2):266~270.
[112] F. Lombardini, J. Ender, L. R??ing, et al. Experiments of Interferometric Layover Solution with the Three-antenna Airborne AER-II SAR System[C].∥Anchorage, Alaska:IGARSS, 2004:3341~3344.
[113] S. M.凯依.现代谱估计原理与应用[M].北京:科学出版社, 1994.
[114]张贤达.现代信号处理(第二版)[M].北京:清华大学出版社, 2002.
[115]王永良,陈辉,彭应宁等.空间谱估计理论与算法[M].北京:清华大学出版社, 2004.
[116]张贤达,保铮.通信信号处理[M].北京:国防工业出版社, 2000.
[117] Jian Li and Petre Stoica. Efficient Mixec-Spectrum Estimation with Applications to Target Feature Extraction[J]. IEEE Trans. Signla Processing, 1996, 44(2): 281~295.
[118] Tong, Wang, Zheng Bao, Zhang Zhen hua, et al. Improving Coherence of Complex Image Pairs Obtained by Along-track Bistatic SARs Using Range-azimuth Prefiltering[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008,46(1):3~13.
[119]王彤,保铮.提高沿航向干涉法性能的最小二乘图像对补偿方法[J].自然科学进展, 2008, 18(12):1484~1490.
[120]王彤,保铮.提高星载SAR-GMTI杂波抑制性能的一种图像均衡方法[C].∥北京:星载SAR/GMTI技术研讨论文集(秘密),2007:25~61.
[121] C.H.Gierull. Digital channel balancing of along-track interferometric SAR data[R]. Defence Research Establishment Ottawa:Technical Memorandum TM 2003-024,2003.
[122] S. Chiu. A Simulation Study of Multi-Channel RADARSAT-2 GMTI[R]. Canada Ottawa: Defence R&D, 2006.
[123] S. Chiu, C.H.Gierull. Multi-channel receiver concepts for radarsar-2 ground moving target indication[C]∥Dresden, Germany: Proceedings of EUSAR’06, 2006.
[124] Richard Klemm. Principles of space-time adaptive processing[M]. London, UK: The institution of Electrical Engineers, 2002.
[125] Soumekh M. Synthetic aperture radar signal processing with MATLAB algorithms[M]. New York: Wiley, 1999: 575~586.
[126] Soumekh M. Moving target detection and imaging using an X band along-track monopulse SAR[J]. Trans. AES, 2002, 38(1): 315~333.
[127]张永胜.星载分布式InSAR概念系统结构与误差研究[D].国防科学技术大学博士学位论文,2007.
[128] Zhang Yong-sheng, Liang Dian-nong, Dong Zhen. Analysis of time and frequency synchronization errors in spaceborne parasitic interferometric SAR system[C]∥Denver, USA: Proc. of the IEEE IGARSS’06, 2006: 3047 - 3050.
[129] Matthias Wei. Time and frequency synchronization aspects for bistatic SAR systems[C]∥Ulm, Germany: EUSAR, 2004: 395~398.
[130] M. Eineder. Oscillator clock drift compensation in bistatic interferometric SAR[C]∥Toulouse, France: IGARSS’03, 2003.
[131] C. H. Gierull, I. C. Sikaneta. Estimating the Effective Number of Looks in Interferometric SAR Data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(8): 1733~1742.
[132] Shen Chiu. SAR along-track interferometry with application to RADARSAT-2 ground moving target indication[C]∥Agia Pelagia: Proceedings of SPIE, Vol. 4885, 2003: 246~255.
[133]周宗潭,董国华,徐昕等.独立成份分析[M].北京:电子工业出版社, 2007.
[134]高贵. SAR图像目标ROI自动获取技术研究[D].长沙:国防科学技术大学电子科学与工程学院, 2007.
[135]罗鹏飞,张文明,刘忠等.统计信号处理基础-估计与检测理论[M].北京:电子工业出版社, 2006.
[136]何友,王国宏,彭应宁等.多传感器信息融合及应用[M].北京:电子工业出版社, 2000.
[137]穆冬.干涉合成孔径雷达成像技术研究[D].南京:南京航空航天大学, 2001.
[138]索志勇,李真芳,保铮等.混合基线InSAR构形下SAR-GMTI方法研究[J].中国科学E辑, 2009, 39(1):1~8.
[139]李真芳,保铮,杨凤凤.基于成像的分布式卫星SAR系统地面运动目标检测(GMTI)及定位技术[J].中国科学E辑:信息科学,2005,35(6):597~609.
[140]吴洪.非均匀杂波环境下相控阵机载雷达STAP技术研究[D].长沙:国防科学技术大学电子科学与工程学院, 2007.
[141] Wiks M C, Rangaswamy M, Adve R., et al. Space-time adaptive processing (A knowledge-based perspective for airborne radar)[J]. IEEE Signal Processing Magazine, 2006: 51~65.
[142] Capraro G T, Farina A, Grifiths H., et al. Knowledge-based radar signal and data processing[J]. IEEE Signal Processing Magazine, 2006:18~29.
[143] Guerci J R, Baranoski E J. Knowledge-aided adaptive radar at DARPA[J]. IEEE Signal Processing Magazine, 2006:41~50.
[144]王永良,彭应宁.空时自适应信号处理[M].北京:清华大学出版社, 2000.
[145] R. Klemm. Space-Time Adaptive Processing: Principles and Applications [M]. London: Proc. IEE Radar-Sonar-Navigation and Avionics, 1998.
[146] Christ D. Richmond. Performance of the Adaptive Sidelobe Blanker Detection Algorithm in Homogeneous Environments[J]. IEEE Trans. Signal Processing, 2000,48(5): 1235~1247.
[147] N. B. Pulsone and C. M. Rader. Adaptive Beamformer Orthogonal Rejection Test[J]. IEEE Trans. Signal Processing, 2001,49(3):521~529.
[148] H. Cox, R. M. Zeskind, and M. H. Owen. Robust adaptive beamforming[J]. IEEE Trans. Acoust., Speech, Signal Processing,1987,35(10):1365~1376.