高分辨SAR/ISAR成像及误差补偿技术研究
|
摘要
高分辨合成孔径雷达和逆合成孔径雷达(SAR/ISAR)成像技术具有全天候、全天时和远距离成像的特点，有效提高了雷达的信息获取能力，具有重要的军用和民用应用价值。
SAR/ISAR成像中，分辨率的提高对精细表征观测目标至关重要。距离分辨率通过发射带宽信号获得，方位分辨率则取决于合成孔径大小。在SAR/ISAR应用中，提高二维分辨率不仅受雷达体制的制约，也对合成孔径的阵列误差更加敏感，需要更为精确稳健的运动补偿。通过合理的频带和时间资源分配，结合相控阵技术的多功能ISAR具备广域、多目标成像的能力。但在多目标探测中，对单一目标的频带和孔径观测将是稀疏有限的，这在信号处理中需要加以克服。结合现代无人机等小型化平台的高精度SAR具有很强的灵活性和机动性，是现代SAR发展的一个重要方向，但低空小型平台对大气扰动更为敏感，且难以配备高精度惯性导航系统进行运动补偿，在成像处理中亟需稳健高效的自适应运动补偿技术。
本论文旨在利用信号处理方法提高SAR/ISAR成像的分辨率、探测区域、灵活性和稳健性，研究内容主要针对目标超分辨成像、稀疏频带和稀疏孔径高分辨成像、精确稳健的自适应运动补偿和多通道SAR宽域高分辨成像四个关键点。论文围绕国家“973”计划课题“稀疏微波成像的理论、体制和方法研究”、国家自然科学基金重大项目“多维度微波成像基础理论与关键技术”以及“863”课题“空间目标雷达宽带特性测量与成像研究”等项目的研究任务，对高分辨SAR/ISAR成像和误差补偿方法进行了研究。全文内容主要针对目标超分辨成像、稀疏频带和稀疏孔径成像，稳健精确的SAR运动补偿自聚焦和多通道SAR成像四个方面，概括为以下四个部分：
第一部分研究基于稀疏重建的目标超分辨成像。建立了基于稀疏重建理论的超分辨成像的一般模型，分析了影响稀疏重建超分辨的若干重要因素及其确定方法。针对低信噪比情况，通过构造加权因子以区分目标信号支撑区和背景，提出了基于改进压缩感知的超分辨重建方法。从贝叶斯压缩感知出发，建立了范数1正则化超分辨成像的一般模型，推导了正则化优化函数中范数权系数的含义及其最大似然估计表达。通过引入同分布和非同分布统计模型，分别提出了贝叶斯超分辨成像和改进贝叶斯超分辨成像算法。建立了分步迭代估计统计参数和超分辨成像重建的处理流程，建立了结合快速傅立叶变换的改进柯西-牛顿求解算法。在此基础上，结合稀疏重建的超分辨算法提出了短孔径ISAR成像、机动目标ISAR成像等多种实用方法，有效提高了ISAR目标成像质量。
第二部分研究稀疏频率和稀疏孔径的高分辨成像。建立了稀疏步进调频信号的高分辨距离像重建优化求解算法。针对稀疏步进调频ISAR运动补偿，结合包络偏移估计、自聚焦以及多频多普勒速度估计等方法提出了稳健精确的统计参数和运动参数估计流程。从贝叶斯统计理论出发，建立了稀疏孔径ISAR成像算法。针对稀疏孔径间存在非连续运动误差，建立了联合高分辨成像和初相校正的优化求解方法，还提出了结合全极点信号模型的稀疏孔径相干化处理方法。所提出的方法改善了ISAR成像雷达的频带和时间资源利用率。
第三部分研究基于扩展相位梯度自聚焦的SAR自适应运动补偿方法。在传统的相位梯度自聚焦算法(PGA)的基础上，提出了局部最大似然-加权相位梯度自聚焦（LML-WPGA）算法，实现对距离空变运动误差精确估计。针对条带式SAR运动补偿，提出了基于WPGA和LML-WPGA的自适应运动补偿方法。该方法分步校正包络偏移误差、非空变相位误差以及空变相位误差，并结合重叠子孔径和低通滤波技术实现条带模式下的高精度全孔径自适应运动补偿，研究中算法还被推广到了大斜视SAR成像处理中。将LML-WPGA的思想推广到两种现有的自聚焦算法(PWE-PGA和WPCA)，建立了LML-PWE-PGA和LML-WPCA算法，极大改善了算法的运算效率和精度。
第四部分研究多通道SAR宽域高分辨成像和通道均衡。在利用多接收通道对空域解多普勒模糊方法系统分析的基础上，提出了基于稳健波束形成的解多普勒模糊成像方法。相比传统的自适应解模糊，基于稳健波束形成的解模糊方法在抑制多普勒模糊分量的同时，实现自适应搜索目标信号的真实导向矢量，有效提高了解模糊算法对多通道SAR信号幅相误差的容忍性。针对存在较大通道误差的情况，提出了距离和方位分维误差校正的自适应通道均衡方法，建立了子空间信号处理的幅相误差估计方法，该方法可有效利用多个甚至所有多普勒单元信号联合估计方位维非空变和慢空变的幅相误差，并在子空间投影中利用天线方向图加权等技术，有效改善了通道误差估计的精度。
High resolution synthetic aperture radar and inverse synthetic aperture radar (SAR/ISAR)imaging technique has the ability of well-weather, day/night and long range applications,which dramatically enhance the capability of information acquisition of modern radar.Therefore, SAR/ISAR technique plays an essential role in many military and civilian fields.
In SAR/ISAR imaging, high resolution is very important to represent the detailedcharacteristic of the target. Range resolution relies on the bandwidth of the transmitted signal,and azimuth resolution depends on the synthetic aperture size. Two-dimension resolution islimited by not only the radar system constraints both also the manifold accuracy of thesynthetic aperture. Generally, with the increase of azimuth resolution, focusing performancewould be very sensitive to the systemetic errors, such as motion errors, demanding precisecompensation schemes. By arranging the radar frequency and time resource suitably andcombining with phased array technique, modern multi-function ISAR accomplishes multiplytasks simutantaneously, such as wide-swath surveillance, multi-target tracking and imaging.However, in this case, the frequency band and aperture for a single target is limited and sparse,which should be accounted in the imaging processing. Owing to its fleasibility andmaneuverability, compact SAR mounted on small platforms, such unmanned aerial vehicleand missile, is very important for modern battlefield survelliance. However, because of itssmall size and light-load capability, it is sensitive to the atmospheric turbulence, andfurthermore, the high-precision inertia navigation system is usually unavailable due to loadcapability constraint of the platforms. Therefore, prcesise and robust motion compensationbased on raw data is desiderated.
This dissertation studies new techniques to improve the resolution, operational swath,feasibility and robustness of SAR/ISAR from four key aspects, i.e. resolution enhancementwith sparse representation, high resolution imaging from sparse frequency bands andapertures, precise and robust motion compensation based on raw data, andhigh-resolution-wide-swath imaging with azimuth multi-channel SAR. The relevant work issupported by by the National Basic Research Program of China （973Program, No.2010CB731903）, National Science Foundation of China (No.60802081and No.60890072)and the National High Technology Research and Development Program of China (No.2008AA8080402).
The main content of this dissertation is summarized as follows.
The first part focuses on the super-resolution imaging based on sparse representation. A general compressive sensing (CS)-based imaging scheme is built. Some related factorsaffecting the performance of the algorithm are analyzed in detail, based on which we alsodevelop the approach to estimating the related parameters. Accounting for the strong noise,the signal and noise supports are distigushed via introducing optimal weigths, and theimproved CS super-resolution imaging method is proposed. Developed from Bayesiancompressive sensing (BCS), we build the norm1-regularition-based super-resolution imagingscheme, and the weighting parameter for norm1term and its maximum likelihood estimationare derivated mathematically. Non-identical statistics model is extended to the BCS-basedoptimization, and two super-resolution algorithms, Bayesian super-resolution and improvedBayesian super-resolution (BSR and IBSR), are developed. A stage-by-stage procedure isdeveloped to jointly estimate statistics parameters and reconstruct the super-resolution image.Combining with fast Fourier transform, we also propose a modified Quasi-Newton solver toBSR and IBSR optimizations. Some applicable approaches for short-aperture ISAR imagingand maneuvering target imaging are also developed. The validity of the proposed methods isproved by several sets of real-measured data.
The second part studies high resolution radar imaging by exploiting sparse frequencybands and apertures. High resolution range profile synthesis by sparse representation and therevelant parameter selection are developed. For ISAR imaging with sparse stepped-frequencywaveforms, precision motion compensation procedure by combining optimal range alignment,autofocusing and parameter estimation with multi-frequency diversity is developed. Based onBayesian compressive sensing, high resolution imaging with exploiting sparse apertures isdeveloped. In the algorithm, the discontinuous phase error function is overcome by sparseaperture coherence processing, which can be jointly implemented in the imaging optimization.In terms of high precision and efficiency, a pre-processing for phase error correction ispresented. Extending from the all-pole model, we develop a novel coherent processing tocorrect the linear and constant phase difference between sub-apertures. Real data sets areutilized to confirm the validation of the proposed methods.
The third part presents the SAR motion compensation (MOCO) based on the extendedphase gradient autofocus (EPGA). In this part, we develop the local maximumlikelihood-weighted phase grandient autofocus (LML-WPGA) algorithm, which is capable ofprecsion estimation of range-dependent phase errors. In terms of precise MOCO for thestrip-map SAR, a procedure implemented by weighted phase gradient autofocus andLML-WPGA is proposed, which corrects nonsystematic range migraition, nonspatial-variantand spatial-variant phase errors sequently. Subaperture overlapping and adaptive filtering areutilized to construct full-aperture motion error function from raw data. The MOCO scheme is extended to highly squinted and spotlight SAR imaging. And LML is also introduced into twoautofocuse PWE-PGA and WPCA. Therefore, LML-PWE-PGA and LML-WPCA aredeveloped, which have the propertities of high precision and efficiency. The proposedalgorithms are validated by using a number of real SAR sets.
The last part focuses on high-resolution-wide-swath (HRWS) imaging withmulti-channel SAR and adaptive channel calibration. Based on detailed analysis on theDoppler ambiguity resolving with spatial filtering beamforming, the robust beamformingtechniques are introduced into multi-channel SAR imaging. Comparing with conventionalDoppler resolving method, robust beamforming-based method can not only suppressambiguity components adaptively, but also precise reconstruct signal component by arrayvector estimation. By the robust beamforming technique, the performance of multi-channelSAR imaging is enhanced effectively. A two-step channel calibration is proposed based on thefact that the amplitude and phase errors between channels are usually uncoupling in range andazimuth directions. Subspace-based calibration is developed to correct the channel mismatch,whose performance and robustness are ensured by using multiply Doppler bins and weightingsubspace projection. Two sets of real measured data are utilized to confirm the effectivenessof the proposed methods.
SAR/ISAR成像中，分辨率的提高对精细表征观测目标至关重要。距离分辨率通过发射带宽信号获得，方位分辨率则取决于合成孔径大小。在SAR/ISAR应用中，提高二维分辨率不仅受雷达体制的制约，也对合成孔径的阵列误差更加敏感，需要更为精确稳健的运动补偿。通过合理的频带和时间资源分配，结合相控阵技术的多功能ISAR具备广域、多目标成像的能力。但在多目标探测中，对单一目标的频带和孔径观测将是稀疏有限的，这在信号处理中需要加以克服。结合现代无人机等小型化平台的高精度SAR具有很强的灵活性和机动性，是现代SAR发展的一个重要方向，但低空小型平台对大气扰动更为敏感，且难以配备高精度惯性导航系统进行运动补偿，在成像处理中亟需稳健高效的自适应运动补偿技术。
本论文旨在利用信号处理方法提高SAR/ISAR成像的分辨率、探测区域、灵活性和稳健性，研究内容主要针对目标超分辨成像、稀疏频带和稀疏孔径高分辨成像、精确稳健的自适应运动补偿和多通道SAR宽域高分辨成像四个关键点。论文围绕国家“973”计划课题“稀疏微波成像的理论、体制和方法研究”、国家自然科学基金重大项目“多维度微波成像基础理论与关键技术”以及“863”课题“空间目标雷达宽带特性测量与成像研究”等项目的研究任务，对高分辨SAR/ISAR成像和误差补偿方法进行了研究。全文内容主要针对目标超分辨成像、稀疏频带和稀疏孔径成像，稳健精确的SAR运动补偿自聚焦和多通道SAR成像四个方面，概括为以下四个部分：
第一部分研究基于稀疏重建的目标超分辨成像。建立了基于稀疏重建理论的超分辨成像的一般模型，分析了影响稀疏重建超分辨的若干重要因素及其确定方法。针对低信噪比情况，通过构造加权因子以区分目标信号支撑区和背景，提出了基于改进压缩感知的超分辨重建方法。从贝叶斯压缩感知出发，建立了范数1正则化超分辨成像的一般模型，推导了正则化优化函数中范数权系数的含义及其最大似然估计表达。通过引入同分布和非同分布统计模型，分别提出了贝叶斯超分辨成像和改进贝叶斯超分辨成像算法。建立了分步迭代估计统计参数和超分辨成像重建的处理流程，建立了结合快速傅立叶变换的改进柯西-牛顿求解算法。在此基础上，结合稀疏重建的超分辨算法提出了短孔径ISAR成像、机动目标ISAR成像等多种实用方法，有效提高了ISAR目标成像质量。
第二部分研究稀疏频率和稀疏孔径的高分辨成像。建立了稀疏步进调频信号的高分辨距离像重建优化求解算法。针对稀疏步进调频ISAR运动补偿，结合包络偏移估计、自聚焦以及多频多普勒速度估计等方法提出了稳健精确的统计参数和运动参数估计流程。从贝叶斯统计理论出发，建立了稀疏孔径ISAR成像算法。针对稀疏孔径间存在非连续运动误差，建立了联合高分辨成像和初相校正的优化求解方法，还提出了结合全极点信号模型的稀疏孔径相干化处理方法。所提出的方法改善了ISAR成像雷达的频带和时间资源利用率。
第三部分研究基于扩展相位梯度自聚焦的SAR自适应运动补偿方法。在传统的相位梯度自聚焦算法(PGA)的基础上，提出了局部最大似然-加权相位梯度自聚焦（LML-WPGA）算法，实现对距离空变运动误差精确估计。针对条带式SAR运动补偿，提出了基于WPGA和LML-WPGA的自适应运动补偿方法。该方法分步校正包络偏移误差、非空变相位误差以及空变相位误差，并结合重叠子孔径和低通滤波技术实现条带模式下的高精度全孔径自适应运动补偿，研究中算法还被推广到了大斜视SAR成像处理中。将LML-WPGA的思想推广到两种现有的自聚焦算法(PWE-PGA和WPCA)，建立了LML-PWE-PGA和LML-WPCA算法，极大改善了算法的运算效率和精度。
第四部分研究多通道SAR宽域高分辨成像和通道均衡。在利用多接收通道对空域解多普勒模糊方法系统分析的基础上，提出了基于稳健波束形成的解多普勒模糊成像方法。相比传统的自适应解模糊，基于稳健波束形成的解模糊方法在抑制多普勒模糊分量的同时，实现自适应搜索目标信号的真实导向矢量，有效提高了解模糊算法对多通道SAR信号幅相误差的容忍性。针对存在较大通道误差的情况，提出了距离和方位分维误差校正的自适应通道均衡方法，建立了子空间信号处理的幅相误差估计方法，该方法可有效利用多个甚至所有多普勒单元信号联合估计方位维非空变和慢空变的幅相误差，并在子空间投影中利用天线方向图加权等技术，有效改善了通道误差估计的精度。
High resolution synthetic aperture radar and inverse synthetic aperture radar (SAR/ISAR)imaging technique has the ability of well-weather, day/night and long range applications,which dramatically enhance the capability of information acquisition of modern radar.Therefore, SAR/ISAR technique plays an essential role in many military and civilian fields.
In SAR/ISAR imaging, high resolution is very important to represent the detailedcharacteristic of the target. Range resolution relies on the bandwidth of the transmitted signal,and azimuth resolution depends on the synthetic aperture size. Two-dimension resolution islimited by not only the radar system constraints both also the manifold accuracy of thesynthetic aperture. Generally, with the increase of azimuth resolution, focusing performancewould be very sensitive to the systemetic errors, such as motion errors, demanding precisecompensation schemes. By arranging the radar frequency and time resource suitably andcombining with phased array technique, modern multi-function ISAR accomplishes multiplytasks simutantaneously, such as wide-swath surveillance, multi-target tracking and imaging.However, in this case, the frequency band and aperture for a single target is limited and sparse,which should be accounted in the imaging processing. Owing to its fleasibility andmaneuverability, compact SAR mounted on small platforms, such unmanned aerial vehicleand missile, is very important for modern battlefield survelliance. However, because of itssmall size and light-load capability, it is sensitive to the atmospheric turbulence, andfurthermore, the high-precision inertia navigation system is usually unavailable due to loadcapability constraint of the platforms. Therefore, prcesise and robust motion compensationbased on raw data is desiderated.
This dissertation studies new techniques to improve the resolution, operational swath,feasibility and robustness of SAR/ISAR from four key aspects, i.e. resolution enhancementwith sparse representation, high resolution imaging from sparse frequency bands andapertures, precise and robust motion compensation based on raw data, andhigh-resolution-wide-swath imaging with azimuth multi-channel SAR. The relevant work issupported by by the National Basic Research Program of China （973Program, No.2010CB731903）, National Science Foundation of China (No.60802081and No.60890072)and the National High Technology Research and Development Program of China (No.2008AA8080402).
The main content of this dissertation is summarized as follows.
The first part focuses on the super-resolution imaging based on sparse representation. A general compressive sensing (CS)-based imaging scheme is built. Some related factorsaffecting the performance of the algorithm are analyzed in detail, based on which we alsodevelop the approach to estimating the related parameters. Accounting for the strong noise,the signal and noise supports are distigushed via introducing optimal weigths, and theimproved CS super-resolution imaging method is proposed. Developed from Bayesiancompressive sensing (BCS), we build the norm1-regularition-based super-resolution imagingscheme, and the weighting parameter for norm1term and its maximum likelihood estimationare derivated mathematically. Non-identical statistics model is extended to the BCS-basedoptimization, and two super-resolution algorithms, Bayesian super-resolution and improvedBayesian super-resolution (BSR and IBSR), are developed. A stage-by-stage procedure isdeveloped to jointly estimate statistics parameters and reconstruct the super-resolution image.Combining with fast Fourier transform, we also propose a modified Quasi-Newton solver toBSR and IBSR optimizations. Some applicable approaches for short-aperture ISAR imagingand maneuvering target imaging are also developed. The validity of the proposed methods isproved by several sets of real-measured data.
The second part studies high resolution radar imaging by exploiting sparse frequencybands and apertures. High resolution range profile synthesis by sparse representation and therevelant parameter selection are developed. For ISAR imaging with sparse stepped-frequencywaveforms, precision motion compensation procedure by combining optimal range alignment,autofocusing and parameter estimation with multi-frequency diversity is developed. Based onBayesian compressive sensing, high resolution imaging with exploiting sparse apertures isdeveloped. In the algorithm, the discontinuous phase error function is overcome by sparseaperture coherence processing, which can be jointly implemented in the imaging optimization.In terms of high precision and efficiency, a pre-processing for phase error correction ispresented. Extending from the all-pole model, we develop a novel coherent processing tocorrect the linear and constant phase difference between sub-apertures. Real data sets areutilized to confirm the validation of the proposed methods.
The third part presents the SAR motion compensation (MOCO) based on the extendedphase gradient autofocus (EPGA). In this part, we develop the local maximumlikelihood-weighted phase grandient autofocus (LML-WPGA) algorithm, which is capable ofprecsion estimation of range-dependent phase errors. In terms of precise MOCO for thestrip-map SAR, a procedure implemented by weighted phase gradient autofocus andLML-WPGA is proposed, which corrects nonsystematic range migraition, nonspatial-variantand spatial-variant phase errors sequently. Subaperture overlapping and adaptive filtering areutilized to construct full-aperture motion error function from raw data. The MOCO scheme is extended to highly squinted and spotlight SAR imaging. And LML is also introduced into twoautofocuse PWE-PGA and WPCA. Therefore, LML-PWE-PGA and LML-WPCA aredeveloped, which have the propertities of high precision and efficiency. The proposedalgorithms are validated by using a number of real SAR sets.
The last part focuses on high-resolution-wide-swath (HRWS) imaging withmulti-channel SAR and adaptive channel calibration. Based on detailed analysis on theDoppler ambiguity resolving with spatial filtering beamforming, the robust beamformingtechniques are introduced into multi-channel SAR imaging. Comparing with conventionalDoppler resolving method, robust beamforming-based method can not only suppressambiguity components adaptively, but also precise reconstruct signal component by arrayvector estimation. By the robust beamforming technique, the performance of multi-channelSAR imaging is enhanced effectively. A two-step channel calibration is proposed based on thefact that the amplitude and phase errors between channels are usually uncoupling in range andazimuth directions. Subspace-based calibration is developed to correct the channel mismatch,whose performance and robustness are ensured by using multiply Doppler bins and weightingsubspace projection. Two sets of real measured data are utilized to confirm the effectivenessof the proposed methods.
引文
[1] A. Hovanessian. Introduction to Synthetic Array and Imaging Radar. Artech House,1980.
[2] J. P. Fitch. Synthetic Aperture Radar. Springer-Verlag New York Inc.,1988.
[3]张澄波.综合孔径雷达.北京:科学出版社，1989.
[4] J. C. Curlander and R. N. McDonough. Synthetic Aperture Radar: System andSignal Processing. Jone Wiley&Sons, INC,1991.
[5] D. R. Wehner. High-Resolution Radar.2nd Edition. Boston, MA: Artech House,Inc.1994.
[6] W. G. Carrara, R. S. Goodman, and R. M. Majewski, Spotlight Synthetic ApertureRadar: Signal Processing Algorithm [M]. Boston, MA: Artech House,1995.
[7] C. V. Jakowatz Jr., D. E. Wahl, P. H. Eichel, D. C. Ghiglia, and P. A. Thompson.Spotlight-Mode Synthetic Aperture Radar: A Signal Processing Approach, Boston:KluwerAcademic Publishers,1996.
[8] M. Soumekh. Synthetic Aperture Radar Signal Processing with MATLABAlgorithms. John Wiley&Sons, Inc.1999.
[9]刘永坦.雷达成像技术.哈尔滨:哈尔滨工业大学出版社，1999.
[10]G. Franceschetti and R. Lanari. Synthetic Aperture Radar Processing, CRC PressBoca Raton, Mar.30,1999.
[11]R. J. Sullivan. Micowave Radar Imaging and Advanced Concepts. Boston: ArtechHouse,2000.
[12]袁孝康.星载合成孔径雷达导论[M].北京:国防工业出版社,2003.
[13]张直中.机载和星载合成孔径雷达导论[M].北京:电子工业出版社,2004.
[14]保铮,邢孟道,王彤.雷达成像技术[M].北京:电子工业出版社,2005.
[15]Ian G. Cumming, Frank H. Wong著,洪文,胡东辉等译.合成孔径雷达成像—算法与实现[M].北京:电子工业出版社,2007.
[16]M. I. Skolnik.王军等译.雷达手册[M].北京:电子工业出版社,2003.
[17]C. Elahci, T. Bicknell, R. L. Jordan, and C. Wu. Spaceborne Synthetic ApertureImaging Radars: Application, Techniques, and Technology [J]. Proc. of IEEE.1982,70(10).1174-1209.
[18]W. M. Brown. Synthetic Aperture Radar [J], IEEE Trans. on AES,1967,3(2).217-229.
[19] W. M. Brown and L.J. Porcello. An Introduction to Synthetic Aperture Radar [J],IEEE Spectrum, Sept.1969, Vol.6.52-62.
[20]C. A. Wiley. Synthetic Aperture Radars [J]. IEEE Trans. on AES,1985,21(3).440-443.
[21]D. R. Wehner. High-Resolution Radar [M],2nd Edition. Boston, MA: ArtechHouse, Inc.1994.
[22]D. L. Mensa. High Resolution Radar Cross-Section Imaging [M]. Artech House,Inc.1991.
[23]B. Borden. Radar Imaging of Airborne Targets: A Primer for AppliedMathematicians and Physicists [M]. Bristol, Philadelphia: Institute of Physics Pub.,1999.
[24]M. J. Pricket, C. C. Chen. Principle of Inverse Synthetic Aperture Radar(ISAR)Imaging [C]. EASCON record, Arlington, VA, Sep.29-Oct.1,1980.340-345.
[25]W. M. Brown. Synthetic Aperture Radar [J]. IEEE Trans. on AES,1967, Vol.3(2).217-229.
[26]C. W. Sherwin, J. P. Ruina, R. D. Rawcliffe. Some Early Developments inSynthetic Aperture Radar Systems [M], IRE Trans. on Military Electronics,1962,Vol.6(2),111-115.
[27]Elahci C, Bicknell T, Jordan R L, and Wu C. Spaceborne Synthetic ApertureImaging Radars: Application, Techniques, and Technology [J]. Proc. of IEEE,1982,70(10):1174-1209.
[28]http://ilrs.gsfc.nasa.gov/satellite_missions/list_of_satellites/seas_general.html.
[29]http://en.wikipedia.org/wiki/Lacrosse
[30]郭华东,王长林.全天候全天时三维航天遥感技术-介绍航天飞机雷达地形测图计划[J],遥感信息,2000,(1):47-48.
[31]http://www.infoterra.de/terrasar-x-satelliteH.
[32]http://www.dlr.de/hr/en/desktopdefault.aspx/tabid-2326/3776_read-5691/.
[33]http://www.fhr.fraunhofer.de/fhr/fhr_c628_f7_en.html.
[34]R. W. Bayma, E. Trujillo, HISARTM COTS-based synthetic aperture radar [A].Digital Avionics Systems Conference,1996:319-325.
[35]S. I. Tsunoda, F. Pace, J. Stence, M. Woodring, Lynx: A High-resolution SyntheticAperture Radar [A], SPIE Aerosense [C],1999, vol.3704,1-8.
[36]http://www.sandia.gov/radar/minisar.html.
[37]J R Bennett, I G Cumming. A Digital Processor for the Production of SeasatSynthetic Aperture Radar Imagery [A]. Proc. SURGE workshop, Frascati,ESA-SP-154,1979.
[38]J R Bennett, I G Cumming, R A Deane. The Digital Processing of Seasat SyntheticAperture Radar Data [A]. IEEE Inter. Radar conf [C]. Washington:1980.168-175.
[39]Munson D C, Jr. OBrien J D, Jenkins W K. A Tomographic Formation of SpotlightMode Synthetic Aperture Radar [J]. Proc. IEEE,1983,71(8):917-925.
[40]C Cafforio, C Prati, F Rocca. Full Resolution Focusing of SEASAT SAR Images inthe Frequency-wave Number Domain [A]. Proc. of the8th EARSeLSymposium[C]. Capri Italy:1988.336-355.
[41]F Rocca, C Cafforio, C Prati. Synthetic Aperture Radar: A New Application forWave Equation Techniques [J]. Geophysical prospecting,1989,37.809-830.
[42]R K Raney, P W Vachon. A Phase Preserving SAR Processor [A]. IGARSS’89[C].1989.2588-2591.
[43]R K Raney, H Runge, R Bamler, I G Cumming, F H Wong. Precision SARProcessing Using Chirp Scaling [J]. IEEE Trans. on GRS,1994,32(4):786-799.
[44]G W Davidson, I G Cumming, M R Ito. A Chirp Scaling Approach for ProcessingSquint Mode SAR Data [J]. IEEE Trans. on AES,1996,32(1):121-133.
[45]Cantafio L J.(Ed.). Space-based Radar Handbook [M]. Boston, Artech House,1989.
[46]G. Krieger and A. Moreira, Spaceborne Bi-and Multistatic SAR: Potential andChallenges [J], IEE Proceedings–Radar, Sonar and Navigation,2006,153(3), pp.184-198.
[47]G. Krieger, N. Gebert, A. Moreira. Multidimensional Waveform Encoding: A NewDigital Beamforming Technique for Synthetic Aperture Radar Remote Sensing.IEEE Trans. on GRS,2008,46(1):31-46.
[48]N. Gebert, G. Krieger, and A. Moreira, Digital Beamforming on Receive:Techniques and Optimization Strategies for High-Resolution Wide-Swath SARImaging [J], IEEE Trans. on AES,2009,45(2),564-592.
[49]G. Krieger, N. Gebert, A. Moreira. Unambiguous SAR Signal Reconstruction FromNonuniform Displaced Phase Center Sampling [J]. IEEE GRSL,2004,1(4):260:264.
[50]Zhenfang Li, Zheng Bao, Hai Li, Guisheng Liao. Image Auto-Coregistration andInSAR Interferogram Estimation Using Joint Subspace Projection [J]. IEEE Trans.on GRS,2006,44(2):288-297.
[51]Zhenfang Li, Zheng Bao, Hongyang Wang, Guisheng Liao. Performanceimprovement for constellation SAR using signal processing techniques [J]. IEEETrans. on AES,2006,42(2):436-452.
[52]N. Goodman, S. Lin, D. Rajakrishna, and J. Stiles, Processing of Multiple-ReceiverSpaceborne Arrays for Wide-Area SAR [J], IEEE Trans. on GRS,40(4), pp.841-852, Apr.2002.
[53]Wang Tong, Bao Zheng，Zhang Zhenghua, Ding Jingshan. Improving Coherence ofComplex Image Pairs Obtained by Along-Track Bistatic SARs UsingRange–Azimuth Prefiltering [J]. IEEE Trans. on GRS,2008,46(1):3–13.
[54]A. Moreira and H. Yonghong, Airborne SAR Processing of Highly Squinted DataUsing a Chirp Scaling Approach with Integrated Motion Compensation [J], IEEETrans. on GRS,1994,32(5), pp.1029-1040.
[55]C. E. Mancill, and J. M. Swiger, A Map Draft Autofocus Technique for CorrectingHigher Order SAR Phase Errors [A],27th Annual Tri-Service Radar SymposiumRecord, Monterey, CA, pp.391-400, June23-25,1981.
[56]M. Xing, X. Jiang, R. Wu, F. Zhou and Z. Bao, Motion Compensation for UAVSAR Based on Raw Radar Data [J], IEEE Trans. on GRS,2009,47(8),2870-2883.
[57]P. Samczy ski, G. Pietrzyk, and A. Gorzelanczyk, Coherent MapDrift Technique[J], IEEE Trans. on GRS,2010,48(3),1505-1517.
[58]D. E. Wahl, P. H. Eichel, D. C. Ghiglia, and C. V. Jakowatz, Jr., Phase GradientAutofocus—A Robust Tool for High Resolution Phase Correction [J], IEEE Trans.on AES,1994,30(3),827–835.
[59]H. L. Chan and T. S. Yeo, Noniterative Quality Phase-Gradient Autofocus (QPGA)Algrotihm for Spotlight SAR Imagery [J], IEEE Trans. on GRS,1998,36(5),1531-1539.
[60]W. Ye, T. S. Yeo and Z Bao, Weighted Least-Squares Estimation of Phase Errorsfor SAR/ISAR Autofocus [J], IEEE Trans. on GRS,1999,37(5),.2487-2494.
[61]X. Li, G. Liu, J. Ni, Autofocusing of ISAR Images Based on Entropy Minimization[J], IEEE Trans. on AES,1999,35(4),1240-1251.
[62]F. Berizzi, G. Cosini, M. Diani, M. Veltroni, Autofocus of Wide Azimuth AngleSAR Images by Contrast Optimization [A], IEEE Radar Conference,1230-1232,1996.
[63]Ausherman Dale A., Kozma Adam, Walker Jack L., Jones Harrison M., PoggioEnrico C.. Developments in Radar Imaging [J]., IEEE Trans. on AES,1984,20（4）,363-400.
[64]D. A. Ausherman, A. Kozma, J.L. Walker, H.M. et al.. Developments in RadarImaging [J], IEEE Trans. on AES,1984,20(4),363-399.
[65]史仁杰,雷达反导与林肯实验室[J].系统工程与电子技术.2007,29(11),1781-1799.
[66]Herbert G. Weiss, The Millstone and Haystack Radars [J]，IEEE Trans. on AES.2001,37(1),365-379.
[67]MIT Lincoln Laboratory2009Annual Report. www.ll.mit.edu.
[68]A Sourcebook for the Use of the FGAN Tracking and Imaging Radar for SatelliteImaging. http://www.fhr.fgan.de/fhr/fhr_en.html.
[69]C. C. Chen and H. C. Andrews. Target-motion-induced Rader Imaging [J]. IEEETrans. on AES,1980,7(16),2-14.
[70]C. Chen, H. C. Andrews. Multifrequency Imaging of Radar Turntable Data [J],IEEE Trans. on AES,1980,16(1),15-22.
[71]M. Soumekh, S. Nugroho. ISAR Imaging of An Airborne DC-9[A]. Proc ICASSP.1993,465-468.
[72]R. Goodman, W, Nagy, Wilelm. A High Fidelity Ground to Air Imaging RadarSystem [A]. IEEE National Radar Conference Record.1994,29-34.
[73]V. C. Chen, S. Qian. Joint Time-Frequency Transform for Radar Range-DopplerImaging [J]. IEEE Trans. on AES,1998,34(2):486-499.
[74]V. C. Chen. Adaptive Time-Frequency ISAR Processing [C]. SPIE1996, Denver,Co, USA,1996:133-140.
[75]S.L.Borison, S.B.Bowling, and K.M.Cuomo, Super-Resolution Methods forWideband Radar [J], Lincoln Lab. J.,1992,5(3)441-461.
[76]T. G. Moore, B. W. Zuerndorfer, and E. C. Burt, Enhanced Imagery UsingSpectral-Estimation-Based Techniques [J], Lincoln Lab. J.,1997,10(2),171–186.
[77]J. Li and P. Stoica,An Adaptive Filtering Approach to Spectral Estimation and SARImaging [J], IEEE Trans. on SP,1996,44(6),1469-1484.
[78]Li J, Stoica P. Efficient Mixed-Spectrum Estimation with Applications to TargetFeature Extraction [J], IEEE Trans. on SP,1996,44(2),281-295.
[79]Z.S.Liu, J.Li, Synthetic Aperture Radar Motion Compensation and FeatureExtraction by Means of A Relaxation-Based Algorithm [J], J. Opt. Soc. Am. A.,1998,15(3),599-610.
[80]K. M. Cuomo, J. E. Piou, and J. T. Mayhan. Ultrawide-Band Coherent Processing[J]. IEEE Trans. on AP.1999,47(6).1097-1107.
[81]L. D. Vann, K. M. Cuomo, J. E. Piou, Multisensor Fusion Processing for EnhancedRadar Imaging [R], Lincoln Lab., MIT, Technical report1056,2000.
[82]D. Pastina, M Bucciarelli and P Lombardo, Multistatic and MIMO DistributedISAR for Enhanced Cross-Range Resolution of Rotating Targets [J], IEEE Trans.on GRS,2010,48(8),3300-3317.
[83]王成，雷达信号层融合成像技术研究[D]，国防科技大学，长沙：2006.
[84]保铮,王根原,罗琳.逆合成孔径雷达的距离-瞬时多普勒成像方法.电子学报.1998,26(12).79-83.
[85]王根原,保铮.一种基于自适应Chirplet分解的逆合成孔径雷达成像方法.电子学报.1999,27(3).29-31.
[1] Q. Zhang and Y. Q. Jin, Aspects of Radar Imaging Using Frequency-Stepped ChirpSignals [J], EURASIP Joural Applied Signal Processing, Vol.2006,2006,1–8,Article ID85823.
[2] T. G. Moore, B. W. Zuerndorfer and E. C. Burt, Enhanced Imagery UsingSpectral-Estimation-Based Techniques [J], Lincoln Lab. J.,10(2),1997,171–186.
[3] J. T. Mayhan, M. L. Burrows, K. M. Cuomo and J. E. Piou, High Resolution3D―Snapshot‖ISAR Imaging and Feature Extraction [J], IEEE Trans. on AES, April2001,Vol.37(2),630-641.
[4] K. Suwa, Toshio Wakayama, and M. Iwamoto, Three-Dimensional TargetGeometry and Target Motion Estimation Method Using Multistatic ISAR Moviesand Its Performance [J], IEEE Trans. on GRS, Janunary2011,45(1),45–54.
[5] S. L. Borison, S. B. Bowling, and K. M. Cuomo, Super-Resolution Methods forWideband Radar [J], Lincoln Lab. J.,1992,5(3),441–461.
[6] J.Gudnason, J. Cui, M. Brookes, HRR Automatic Target Recognition FromSuperresolution Scattering Center Features [J], IEEE Trans. on AES,2009,45(4),1512-1524.
[7] L. M. Novak, G. J. Owirka, and A. L. Weaver, Automatic Target Recognition UsingEnhanced Resolution SAR Data [J], IEEE Trans. On AES,1999,35(1),157–175.
[8] H. J. Li, N. H. Farhat, and Y. S. Shen, A New Iterative Algorithm for Extrapolationof Data Available in Multiple Restricted Regions with Applications to RadarImaging [J], IEEE Trans. on AP, May1987,35(5),581–588.
[9] K. Suwa, and M. Iwamoto, A Two-Dimensional Bandwidth ExtrapolationTechnique for Polarimetric Synthetic Aperture Radar Images [J], IEEE Trans. onGRS,45(1), Janurary2007,45–54.
[10]I. J. Gupta, High-Resolution Radar Imaging Using2-D Linear Prediction [J], IEEETrans. on AP,42(1), January1994,31–37.
[11]T. G. Moore, B. W. Zuerndorfer, and E. C. Burt, Enhanced Imagery UsingSpectral-Estimation-Based Techniques [J], Lincoln Lab. J.,1997,10(2),171–186.
[12]R. O. Lane, K. D. Copsey, A. R. Webb, A Bayesian Approach to SimultaneousAutofocus and Super-Resolution [J], Proceedings of SPIE, Vol.5427, April2004,133-142.
[13]A. Mohammad-Djafari and G. Demoment, Maximum Entropy Fourier Synthesiswith Application to Diffraction Tomography [J], Appl. Opt., Vol.26,1989,1745-1754.
[14]Li, J., and Stoica, P. Efficient Mixed-Spectrum Estimation with Applications toTarget Feature Extraction [J], IEEE Trans. on SP, February1996,44(2),281-295.
[15]Bi, Z., Li, J., and Liu, Z. S., Super Resolution SAR Imaging Via ParametricSpectral Estimation Methods [J], IEEE Trans. on AES, Janurary1999,35(1),267-281.
[16]A. D. Lazarov, Iterative Minimum Mean Square Error Method and RecurrentKalman Procedure for ISAR Image Reconstruction [J], IEEE Trans. on AES,2001,37(4),1432-1441.
[17]Z. S. Liu, R. Wu, J. Li, Complex ISAR Imaging of Maneuvering Targets Via theCapon Estimator [J], IEEE Trans. on SP,1999,47(5),1262-1271.
[18]M. R. Palsetia and J. Li, Using APES for Interferometric SAR Imaging [J], IEEETrans. on IP,1998,7(9),1340–1353.
[19]Li, J., and Stoica, P., An Adaptive Filtering Approach to Spectral Estimation andSAR Imaging [J], IEEE Trans. on SP,1996,44(2),1469-1484.
[20]H. C. Stankwitz, R. J. Dallaire, and J. R. Fienup, Nonlinear Apodization forSidelobe Control in SAR Imagery [J], IEEE Trans. on AES,1995,31(1),267–279.
[21]X. Xu and R. M. Narayanan, Enhanced Resolution in SAR/ISAR Imaging UsingIterative Sidelobe Apodization [J], IEEE Trans. on IP,2005,14(4),537-547.
[22]J. Tsao, and B. D. Steinberg, Reduction of Sidelobe and Speckle Artifacts inMicrowave Imaging: The CLEAN Technique [J], IEEE Trans. on AP,1988,36(4),1688-1697.
[23]R. Bose, A. Freeman, B. D. Steinberg, Sequence CLEAN: A ModifiedDeconvolution Technique for Microwave Images of Contiguous Targets [J], IEEETrans. on AES,2002,38(1),89-96.
[24]E. Cand`es, J. Romberg, and T. Tao, Robust Uncertainty Principles: Exact SignalReconstruction From Highly Incomplete Frequency Information [J], IEEE Trans.on IT,2006,52(2),489–509.
[25]E. Cand`es, J. Romberg, and T. Tao, Near-Optimal Signal Recovery From RandomProjections: Universal Encoding Strategies?[J], IEEE Trans. on IT,2006,52(2),489–509.
[26]D. Donoho, Compressed Sensing [J], IEEE Trans. on IT,2006,52(4),5406–5425.
[27]Zweig, G., Super-Resolution Fourier Transforms by Optimization and ISARImaging [J], IEE Proc-RSN, Vol.150(4), July2003,247-252.
[28]C. W. Zhu, Stable Recovery of Sparse Signals Via Regularized Minimization [J],IEEE Trans. on IT,2008,54(7),3364–3367.
[29]E. van den Berg and M. P. Friedlander, In Pursuit of A Root [R], Tech. Rep.TR-2007-19, Department of Computer Science, University of British Columbia,June2007, http://www.optimization-online.org/DB_HTML/2007/06/1708.html.
[30]M. etin and W. C. Karl, Feature-Enhanced Synthetic Aperture Radar ImageFormation Based on Nonquadratic Regularization [J], IEEE Trans. on IP,2001,10(4),623-631.
[31]M. etin, Feature-Enhanced Synthetic Aperture Radar Imaging [D], BostonUniversity，Docter Dessertion，2001.
[32]Joachim H.G. Ender,On Compressive Sensing Applied to Radar [J], SignalProcessing,2010,90(5),1402-1414.
[33]Matthew A. Herman, Thomas Strohmer. High-Resolution Radar via CompressedSensing [J]. IEEE Trans. on SP,2009,57(6),2275-2284.
[34]X. X. Zhu, R. Bamler, Tomographic SAR Inversion By l1-norm Regularization-TheCompressive Sensing Approach [J], IEEE Trans. on GRS,2009,48(10),3839-3846.
[35]Alessandra Budillon, Annarita Evangelista, and Gilda Schirinzi, Three-DimensionalSAR Focusing From Multipass Signals Using Compressive Sampling [J], IEEE.Trans. on GRS,2011,49(1),488–499.
[36]Y. Wang, H. Ling, V. C. Chen, ISAR Motion Compensation via Adaptive JointTime-Frequency Techniques [J], IEEE Trans. on AES,1998,34(2),670-677.
[37]W. Ye, T. S. Yeo, and Z. Bao, Weighted Least Squares Estimation of Phase Errorsfor SAR/ISAR Autofocus [J], IEEE Trans. on GRS,1999,37(5).2487-2494.
[38]J. Wang and D. Kasilingam, Global Range Alignment for ISAR [J], IEEE Trans. onAES,2003,39(1),351–357.
[39]T. Sauer and A. Schroth, Robust Range Alignment Algorithm Via Hough Transformin An ISAR Imaging System [J], IEEE Trans. on AES,1995,31(3),1173–1177.
[40]D. Zhu, L. Wang, Y. Yu, Q. Tao, and Z. Zhu, Robust ISAR Range Alignment ViaMinimizing the Entropy of the Average Range Profile [J], IEEE GRSL,2009,6(2),204-208.
[41]Q. Zhang, T. S. Yeo, Estimation of Three-Dimensional Motion Parameters inInterferometric ISAR Imaging [J], IEEE Trans. on GRS,2004,42,292-300.
[42]T. Thayaparan, L. Stankovic, C. Wernik, and M. Dakovic, Real-Time MotionCompensation, Image Formation and Image Enhancement of Moving Targets inISAR and SAR Using S-method Based Approach [J], IET Signal Processing,2008,2(3),247-264.
[43]保铮,邢孟道,王彤.雷达成像技术[M].北京：电子工业出版社。
[44]L. Zhang, M. D. Xing, C.W. Qiu, J. Li, Z. Bao, Achieving Higher Resolution ISARImaging with Limited Pulses via Compressed Sampling [J], IEEE GRSL,2009,6(3),567-571.
[45]M. Grant, S. Boyd, and Y. Ye, cvx: Matlab Software for Disciplined ConvexProgramming [R],[online]. Available: http://www.stanford.edu/~boyd/cvx/.
[46]S. Chen, D. Donoho, and M.A. Saunders, Atomic Decomposition by Basis Pursuit[J], SIAM J. Sci Comp.,1999,20(1),33–61.
[47]Thomas Blumensath and Mike E. Davies, Gradient Pursuits [J], IEEE Trans. on SP,2008,56(6),2370-2382.
[48]Tropp, J.A.; Gilbert, A.C. Signal Recovery from Random Measurements ViaOrthogonal Matching Pursuit [J], IEEE Trans. on IT,2007,53(12),4655-4666.
[49]L. Applebaum, S. Howard, S. Searle, and R. Calderbank, Chirp Sensing Codes:Deterministic Compressed Sensing Measurements for Fast Recovery [J], Appl.Comput. Harmonic Anal.,2008,26(2),283-290.
[50]E. Candès, J. Romberg, and T. Tao, Stable Signal Recovery From Incomplete andInaccurate Measurements [J], Comm. Pure Appl. Math,2006,59(8),1027-1223,.
[51]L. Zhang, M. D. Xing, C.W. Qiu, J. Li, J. Sheng, Y. Li, Z. Bao, ResolutionEnhancement for Inversed Synthetic Aperture Radar Imaging under Low SNR viaImproved Compressive Sensing [J], IEEE Trans. on GRS,2010,48(10),3824-3838,.
[52]S. Ji, Y. Xue and L. Carin, Bayesian Compressive Sensing [J], IEEE Trans. on SP,2008,56(6),2346–2356.
[53]S.D. Babacan, R. Molina, and A.K. Katsaggelos, Bayesian Compressive SensingUsing Laplace Priors [J], IEEE Trans. on IP,2010,19(1),53–63.
[54]E. van den Berg and M. P. Friedlander, In pursuit of a root [R], Tech. Rep.TR-2007-19, Department of Computer Science, University of British Columbia,June2007,: http://www.optimization-online.org/DB_HTML/2007/06/1708.html
[55]E. Candès, and M. Wakin, B., Enhancing Sparsity by Reweighted l1Minimization[J], Journal of Fourier Analysis and Applications special issue on sparsity,December2008,14(5),877-905,.
[56]H. Rohling, Radar CFAR Thresholding in Clutter and Multiple Target Situations [J],IEEE Trans. on AES,1983,19,608-621.
[57]G. Davidson, Radar toolbox, Available: http://www.radarworks.com/software.htm.
[58]P. R. Wu, A Criterion for Radar Resolution Enhancement with Burg Algorithm [J],IEEE Trans. on AES,1995,31(2),877-915.
[59]J. F. Sturm. Using SeDuMi1.02, a Matlab toolbox for optimization over symmetriccones. Technical report, Department of Econometrics, Tilburg University, Tilburg,The Netherlands, August1998–October2001.
[60]D. L. Donoho ect.. Sparselab. http://sparselab.stanford.edu/,2007.
[61]Y. Zhang,―YALL1,‖http://www.caam.rice.edu/~optimization/L1/YALL1/.
[62]C. R. Vogel and M. E. Oman, Fast, Robust Total Variation-Based Reconstruction ofNoisy, Blurred Images [J], IEEE Trans. on IP, Vol.7,1998, pp.813–824.
[63]L. Du, H. W. Liu, Z. Bao and M. Xing, Radar HRRP Target Recognition Based onHigher-Order Spectra [J], IEEE Trans. on SP,2005,53(7),2359-2368.
[64]G. Yu, and G. Sapiro, Statistical Compressive Sensing of Gaussian Mixture Models[J], http://arxiv.org/abs/1010.4314,2010.
[1] S. L. Borison, S. B. Bowling, and K. M. Cuomo, Super-Resolution Methods forWideband Radar[J], Lincoln Lab. J.,1992,5(3),441–461.
[2] Q. Zhang and Y. Q. Jin, Aspects of Radar Imaging Using Frequency-Stepped ChirpSignals [J], EURASIP J. Appl. Signal Process.,2006,1–8, Article ID85823.
[3] G. S. Gill, Step Frequency Waveform Design and Processing for Detection ofMoving Targets in Clutter [A], in Proc. IEEE Int. Radar Conf., May8–11,1995,573–578.
[4] R. Barvainis, J.A. Ball, R.P. Ingalls, and J.E. Salah. The Haystack Observatoryλ3-mm Upgrade. Publ.Astron. Soc. Pac.1993,105(693),1334–1341.
[5] Technology in Support of National Security [R]. MIT Lincoln Laboratory Report2010,12-13.
[6] A. Freedman, R. Bose, and B. D. Steinberg, Thinned Stepped FrequencyWaveforms to Furnish Existing Radars with Imaging Capability [J], IEEE Aerosp.Electron. Syst. Mag.,1996,11(11),39–43.
[7] A. Freedman, R. Bose, and B. D. Steinberg, Thinned Stepped FrequencyWaveforms to Furnish Existing Radars with Imaging Capability [J], IEEE AESMagazine,1996,11(11),39–43.
[8] R. Bose, A. Freeman and B. D. Steinberg, Sequence CLEAN: A ModifiedDeconvolution Technique for Microwave Images of Contiguous Targets [J], IEEETrans. on AES,2002,38(1),89-96.
[9] H. J. Li, N. H. Farhat, and Y. S. Shen, A New Iterative Algorithm for Extrapolationof Data Available in Multiple Restricted Regions with Applications to RadarImaging [J], IEEE Trans. on AP,1987,35(5),581–588.
[10] K. Suwa, and M. Iwamoto, A Two-Dimensional Bandwidth ExtrapolationTechnique for Polarimetric Synthetic Aperture Radar Images [J], IEEE Trans. onGRS,2007,45(1),45–54.
[11] I. J. Gupta, High-resolution radar imaging using2-D linear prediction [J], IEEETrans. on AP,1994,42(1),31–37.
[12] T. G. Moore, B. W. Zuerndorfer and E. C. Burt, Enhanced Imagery UsingSpectral-Estimation-Based Techniques [J], Lincoln Lab. J.,1997,10(2),171–186.
[13] S. L. Borison, S. B. Bowling, and K. M. Cuomo, Super-resolution methods forwideband radar [J], Lincoln Lab. J.,1992,5(3),441–461.
[14] K. M. Cuomo, J. E. Piou, and J. T. Mayhan, Ultrawide-Band Coherent Processing[J], IEEE Trans. on AP.1999,47(6),1097-1107.
[15] Li, J., and Stoica, P. Efficient Mixed-Spectrum Estimation with Applications toTarget Feature Extraction [J], IEEE Trans. on SP,1996,44(2):281-295.
[16] Bi, Z., Li, J., and Liu, Z.-S. Super Resolution SAR Imaging via ParametricSpectral Estimation Methods [J]. IEEE Trans. on AES,1999,35(1):267-281.
[17] Z. S. Liu, R. Wu, J. Li: Complex ISAR Imaging of Maneuvering Targets via theCapon Estimator [J], IEEE Trans. on SP,1999,47(5),1262-1271.
[18] E. G. Larsson, P. Stoica, J. Li, Amplitude Spectrum Estimation forTwo-Dimensional Gapped Data [J], IEEE Trans. on SP,2002,50(6),1343-1353.
[19] M. Cetin and R. L. Moses. SAR Imaging from Partial-Aperture Data withFrequency-Band Omissions [C]. SPIE Defense and Security Symposium,Algorithm for Synthetic Aperture Radar Imaging Ⅻ, Orlando, Florida, March2005.
[20] M. Cetin and W. C. Karl. Feature-Enhanced Synthetic Aperture Radar ImageFormation Based on Nonquadratic Regularization [J]. IEEE Trans. on IP.2001,10(4),623-631.
[21] Joachim H.G. Ender, On Compressive Sensing Applied to Radar [J], SignalProcessing,2010,90(5),1402-1414.
[22] E. Candès, J. Romberg, and T. Tao, Robust Uncertainty Principles: Exact SignalReconstruction from Highly Incomplete Frequency Information [J], IEEE Trans.on IT,52(2),489–509,2006.
[23] E. Candès, J. Romberg, and T. Tao, Near-Optimal Signal Recovery From RandomProjections: Universal Encoding Strategies?[J], IEEE Trans. on IT,2006,52(2),489–509.
[24] D. Donoho, Compressed Sensing [J], IEEE Trans. on IT, April2006,52(4),5406–5425.
[25] L. Zhang, M. Xing, C. Qiu, J. Li and Z. Bao., Achieving Higher Resolution ISARImaging with Limited Pulses via Compressed Sampling [J], IEEE. GRSL,2009,6(3),567-571.
[26] K. R. Varshney, M. etin, J. W. Fisher and A. S. Willsky, Sparse Representation inStructured Dictionaries with Application to Synthetic Aperture Radar [J], IEEETrans. on SP,2008,56(8),3548-3561.
[27] A. C. Gurbuz, J. H. McClellan and W.R. Scott, A Compressive Sensing DataAcquisition and Imaging Method for Stepped Frequency GPRs [J], IEEE Trans. onSP,2009,57(7),2640-2650.
[28] X. Zhu, R. Bamler, Tomographic SAR Inversion by L1-norm Regularization-theCompressive Sensing Approach [J], IEEE Trams on GRS,2010,48(10),3839-3846.
[29] S. Ji, Y. Xue and L. Carin, Bayesian Compressive Sensing [J], IEEE Trans. on SP,2008,56(6),2346–2356.
[30] F. Berizzi, M. Martorella, A. Cacciamano, and A. Capria, A Contrast-basedAlgorithm for Synthetic Range-Profile Motion Compensation [J], IEEE Trans. onGRS,2008,46(10),3053–3062.
[31] H. Chen, Y. Liu, W. Jiang, and G.. Guo, A New Approach for Synthesizing theRange Profile of Moving Targets via Stepped-Frequency Waveforms [J], IEEEGRSL,2006,3(3),406–409.
[32] H. Rohling, Radar CFAR Thresholding in Clutter and Multiple Target Situations[J], IEEE Trans. on AES,1983,19,608-621.
[33] G. Davidson, Radar toolbox, Available: http://www.radarworks.com/software.htm.
[34] S.P. Boyd and L. Vandenberghe. Convex Optimization [M]. Cambridge UniversityPress,2004.
[35] O. Axelsson, Iterative Solution Methods [M], Cambridge University Press,1994.
[36] Y. Wang, H. Ling., and V. C. Chen, ISAR Motion Compensation via AdaptiveJoint Time-Frequency Techniques [M], IEEE Trans. on AES,1998,34(2),670-677.
[37] J. Wang and D. Kasilingam, Global Range Alignment for ISAR [J], IEEE Trans.on AES,2003,39(1),351–357.
[38] D. Zhu, L. Wang, Y. Yu, Q. Tao, and Z. Zhu, Robust ISAR Range Alignment viaMinimizing the Entropy of the Average Range Profile [J], IEEE GRSL,2009,6(2),204-208.
[39] W. Ye, T. S. Yeo, and Z. Bao, Weighted Least-Squares Estimation of Phase Errorsfor SAR/ISAR Autofocus [J], IEEE Trans. on GRS, September.1999, Vol.37(5),2487-2494.
[40] D. E. Wahl, P. H. Eichel, D. C. Chiglia,et al. Phase Gradient Autofocus—a RobustTool for High Resolution SAR Phase Correction [J], IEEE Trans. on AES,1994,30(3),827-834.
[41] Berizzi, and Cosini, G. Autofocusing of Inverse Synthetic Aperture Radar ImagesUsing Contrast Optimization [J], IEEE Trans. on AES, July1996,32(3),1185-1191.
[42] X. Li, G. S. Liu, J. L. Ni, Autofocusing of ISAR Images Based on EntropyMinimization [J], IEEE Trans. on AES, October1999,35(4),1240-1251.
[43] Y. Li, M. Xing, L. Zhang and Z. Bao, Detection, Parameter Estimation andImaging of Maneuvering Target in Wide-band Signal [J], Sci. China Ser. F-Inf Sci.,2009,52(6),1015-1026.
[44] S. Zhu, G. Liao, Y. Qu, X. Liu, and Z. Zhou, A New Slant-Range VelocityAmbiguity Resolving Approach of Fast Moving Targets for SAR System [J], IEEETrans. on GRS,2010,48(1).
[45] G. Y. Wang, X. G. Xia, V. C. Chen, Radar Imaging of Moving Targets in FoliageUsing Multifrequency Multiaperture Polarimetric SAR [J], IEEE Trans. on GRS,2003,41(8),1755-1764.
[46] G. Wang, X. Xia, V. C. Chen and R. L. Fiedler, Detection, Location, and Imagingof Fast Moving Targets Using Multifrequency Antenna Array SAR [J], IEEE Trans.on AES,2004,40(1),345-354.
[47]王琦，空间目标ISAR成像的研究[D]，西安：西安电子科技大学，2007.
[48]臧博，张磊，唐禹，邢孟道，逆合成孔径成像激光雷达低信噪比稀疏多孔径成像方法研究[J]，电子与信息学报，2010，32(12),2808-2813.
[49] K. M. Cuomo, J. E. Piou, and J. T. Mayhan. Ultrawide-Band Coherent Processing[J]. IEEE Trans. on AP.1999,47(6).1097-1107.
[50] D. Pastina, M Bucciarelli and P Lombardo,Multistatic and MIMO DistributedISAR for Enhanced Cross-Range Resolution of Rotating Targets [J], IEEE Trans.on GRS,2010,48(8),3300-3317.
[51]王成，雷达信号层融合成像技术研究[D]，国防科技大学，长沙：2006.
[1] W. G. Carrara, R. S. Goodman, and R. M. Majewski, Spotlight Synthetic ApertureRadar: Signal Processing Algorithm [M]. Boston, MA: Artech House,1995.
[2] G. Fornaro, Trajectory Deviations in Airborne SAR: Analysis and Compensation [J],IEEE Trans. on AES,1999,35(3),997-1009.
[3] A. Moreira and H. Yonghong, Airborne SAR Processing of Highly Squinted DataUsing a Chirp Scaling Approach with Integrated Motion Compensation [J], IEEETrans. on GRS,1994,32(5),1029-1040.
[4] M. Xing, X. Jiang, R. Wu, F. Zhou and Z. Bao, Motion Compensation for UAVSAR Based on Raw Radar Data [J], IEEE Trans. on GRS,2009,47(8),2870-2883.
[5] G. Fornaro, G. Franceschetti, and S. Perna, On Center-Beam Approximation inSAR Motion Compensation [J], IEEE Trans. on GRS,2006,3(2),276–280.
[6] M. Y. Lin and C. Wu, A SAR Correlation Algorithm Which Accommodates LargeRange Migration [J], IEEE Trans. on GRS, November,1984, Vol.22,592–597.
[7] J. L. Walker, Range-Doppler Imaging of Rotating Objects [J], IEEE Trans. on AES,1980,16(1),670-677.
[8] I. Cumming, F. Wang, Digital Processing of Synthetic Aperture Radar Data:Algorithm and Implementation [M], Norwood, MA: Artech House,2005.
[9] R. K. Raney, H. Runge, R. Bamler, I. G. Cumming, and F. H. Wong, Precision SARProcessing Using Chirp Scaling [J], IEEE Trans. on GRS,1994,32(4),786–799.
[10] F. Wong, I. Cumming, and R. K. Ranley, Processing Simulated RADARSAT SARData with Squint by a High Precision Algorithm [A], Proc. IEEE Geosci. RemoteSensing Symp.,1176–1178,1993.
[11] G. W. Davidson, A Chirp Scaling Approach for Processing High Squint ModeSAR Data [J], IEEE Trans. on AES,1996,32(1):121–133.
[12] J. Mittermayer, A. Moreira, and O. Loffeld, Spotlight SAR data processing usingthe frequency scaling algorithm [J], IEEE Trans. on GRS,1999,37(4):2198–2214.
[13] J. Mittermayer, A. Moreira, and O. Loffeld, Spotlight SAR Data Processing Usingthe Frequency Scaling Algorithm [J], IEEE Trans. on GRS,1999,37(5):2198–2214.
[14] D. E. Wahl, P. H. Eichel, D. C. Ghiglia and C. V. Jakowatz, Phase GradientAutofocus—A Robust Tool for High Resolution Phase Correction [J], IEEE Trans.on AES,1994,30(3):827–835.
[15] K. A. C. de Macedo, R. Scheiber and A Moreira, An Autofocus Approach forResidual Motion Errors with Application to Airborne Repeated-pass SARInterferometry [J], IEEE Trans. on GRS,2008,46(10):3151-3162.
[16] H. L. Chan and T. S. Yeo, Noniterative Quality Phase Gradient Autofocus (QPGA)Algrotihm for Spotlight SAR Imagery [J], IEEE Trans. on GRS,1998,36(5):1531-1539.
[17] W. Ye, T. S. Yeo and Z Bao, Weighted Least-Squares Estimation of Phase Errors forSAR/ISAR Autofocus [J], IEEE Trans. on GRS,1999,37(5):2487-2494.
[18] J. H. Callow, Signal Processing for Synthetic Aperture Sonar Image Enhancement
[D], New Zealand, Chirstchurch: Canterbury University,2003.
[19] D. E. Wahl, C. V. Jakowatz, Jr. P. A. Thompson, and D. C. Ghiglia, New Approachto Strip-Map SAR Autofocus [A], in Proc.6thIEEE Digital Signal Process.Workshop, Yosemite National Park, CA,1994:53-56.
[20] M. P. Hayes, H. J. Callow, and P. T. Gough, Stripmap Phase Gradient Autofocus
[C], in Proc. OCEANS, September,22–26,2003,52414–2421.
[21] P. T. Gough, M. P. Hayes, and D. R. Griffiths, Strip-map Path Correction UsingPhase Matching Autofocus [A], in Proc.5thECUA, Lyon, France, July,2000:412-418.
[22] S. N. Madsen, Estimating the Doppler Centriod of SAR Data [J], IEEE Trans. onAES,1989,25(2),134-140.
[23] F. H. Wang and I. G. Cumming, A Combined SAR Doppler Centroid EstimationScheme Based upon Signal Phase [J], IEEE Trans. on GRS,1996,34(3),696–707.
[24] I. G. Cumming, A Spatially Selective Approach to Doppler Estimation forFrame-Based Satellite SAR Processing [J], IEEE Trans. on GRS,1996,42(6),1135-1148.
[25] D. G. Thompson, J. S. Bates, D. V. Arnold, and D. G. Long, Extending the phasegradient autofocus algorithm for low-altitude stripmap mode SAR [A], in ProcIGARSS, Hamburg, Germany, July1999:564-566.
[26] J Moreira, Estimating the Residual Error of the Reflectivity Displacement Methodfor Aircraft Motion Error Extraction from SAR Raw Data [A], Record of the IEEE1990International Radar Conference.1990:70-75.
[27] P. Prats, A. Reigber, and J. J. Mallorqui, Topography-Dependent MotionCompensation for Repeat-pass Interferometric SAR Systems [J], IEEE GRSL,2005,2(2),206–210.
[28] K. A. C. de Macedo and R. Scheiber, Precise Topography-and Aperture DependentMotion Compensation for Airborne SAR [J], IEEE GRSL,2005,2(2),172–176.
[29] R. Scheiber and V. Bothale, Interferometric Multi-Look Techniques for SAR Data[A], in Proc. IEEE IGARSS, Toronto, ON, Canada, June,24–28,2002,1,173–175.
[30] N. Ahmed, T. Natarajan, and K. R. Rao, On Image Processing and a DiscreteCosine Transform [J], IEEE Trans. on Comput.,1974， C-23(1),90–93,.
[31] S. Mallat, A Theory for Multiresolution Signal Decomposition: The WaveletRepresentation [J], IEEE Trans. on PAMI, July1989, Vol.11(7):674–693.
[32] D. L. Donoho and I. M. Johnstone, Adapting to Unknown Smoothness via WaveletShrinkage [J], J. Amer. Statist. Assoc.,1995,90:1200–1224.
[33]黄源宝，机载合成孔径雷达成像算法及运动补偿的研究[D]，西安：西安电子科技大学，2005.
[34] F. H. Wong and T. S. Yeo, New Applications of Non-Linear Chirp Scaling in SARData Processing [J], IEEE Trans. on GRS,2001,39(5):946-953.
[35] T. S. Yeo, N. L. Tan, C. B. Zhang and Y. H. Lu, A New Subaperture Approach toHigh Squint SAR Processing [J], IEEE Trans. on GRS,2001,39(5):954-968.
[36]保铮，邢孟道，王彤，雷达成像技术[M]，北京：电子工业出版社，2005.
[37] G. Franceschetti and R. Lanari, Synthetic Aperture Radar Processing [M]. BocaRaton, FL: CRC Press,1999.
[38] P. Samczy ski, G. Pietrzyk, and A. Gorzelanczyk, Coherent MapDrift technique [J],IEEE Trans. on GRS,2010,48(3):1505-1517.
[1] Zhenfang Li, Zheng Bao, Hongyang Wang and Guisheng Liao, PerformanceImprovement for Constellation SAR Using Signal Processing Techniques [J], IEEETrans. on AES,2006,42(2),436-452.
[2]李真芳,保铮,分布式小卫星SAR系统地面运动目标检测方法[J],电子学报,2005,33(9),1664-1666.
[3] Gerhard Krieger, Nicolas Gebert and Alberto Moreira, Unambiguous SAR SignalReconstruction From Nonuniform Displaced Phase Center Sampling [J], IEEEGRSL,2004,1(4),260-264.
[4] A. Currie and M. A. Brown, Wide-swath SAR [J], IEE Proc. Inst. Elect. Eng. F.,1992,139(2),122-135.
[5] G. D. Callaghan and I. D. Longstaff, Wide Swath Spaceborne SAR Using a QuadElement Aray [J], IEE Proc. RSN, June1999,146(3),159-165.
[6] N. A. Goodman, S. C. Lin, D. Rajakrishna and J. M. Stiles, Processing of MultipleReceiver, Spaceborne Arrays for Wide-Area SAR, IEEE Trans. on GRS,2002,40(4),841-852.
[7]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，2006.
[8] Zhenfang Li, Hongyan Wang, Zheng Bao, Generation of Wide-Swath andHigh-Resolution SAR Images From Multichannel Small Spaceborne SAR System[J], IEEE GRSL,2005,2(1),82-86.
[9] Kim J., Younis M., Becker D., Wiesbeck W., Experimental Performance Analysis ofDigital Beamforming on Synthetic Aperture Radar [A], in7th European Conferenceon Synthetic Aperture Radar, CD-ROM, Friedrichshafen, Germany, June2008.
[10]张贤达，现代信号处理[M]，北京：清华大学出版社，2005.
[11]井伟，星载SAR宽场景高分辨成像技术研究[D]，西安：西安电子科技大学，2008.
[12]J. Li, P. Stoica, Robust Adaptive Beamforming [M], John Wiley&Sons, Inc.,Hoboken, New Jersey,2006.
[13]Sergiy A. Vorobyov, Alex B. Gershman, and Zhi-Quan Luo, Robust AdaptiveBeamforming Using Worst-Case Performance Optimization: A Solution to theSignal Mismatch Problem [J], IEEE Trans. on SP,2003,51(2),313-324.
[14]J. Li, P. Stoica and Z. Wang, On Robust Capon Beamforming and DiagonalLoading [J], IEEE Trans. on SP,2003,51(7),1702-1715.
[15]P. Stoica, Z. Wang and J. Li, Robust Capon Beamforming [J], IEEE SPL,2003,10(6),172-175.
[16]J. Li, P. Stoica and Z. Wang, Doubly Constrained Robust Capon Beamformer [J],IEEE Trans. on SP,2004,52(9),2407-2423.
[17]Niolas Gebert, Gerhard Krigeger, Alberto Moreira, Digital Beamforming onReceive: Techniques and Optimization Strategies for High-Resolution Wide-SwathSAR Imaging [J], IEEE Trans. on AES,2009,45(2),564-592.
[18]L. Ma, Z. Li and S. Liao, System Error Analysis and Calibration Methods ForMulti-Channel SAR [A], Progress In Electromagnetics Research, Vol.112,309-327,2011
[19]Nicolas Gebert, Felipe Queiroz de Almeida, Gerhard Krieger, AdvancedMulti-Channel SAR Imaging–Measured Data Demonstration [A], In: Proceedingsof the International Radar Symposium (IRS), Seiten525-529,2009-09-09,Hamburg, Germany.
[20]Friedlander B.，A Subspace Method for Space Time Adaptive Processing [J], IEEETrans. on SP,2005, Vol.53(1),74-82.
[21]王永良，陈辉，彭应宁，万群，空间谱估计理论与算法[M]，北京：清华大学出版社，2004.
[22]L. Zhang, M. Xing, C. Qiu and Z. Bao, Adaptive Two-step Calibration forHigh-Resolution and Wide-swath SAR imaging [J], IET Radar Sonar Navig.,2010,4(4),548-559.
[23]Wang, B. H., Guo. Y., Mutual Coupling Auto-Calibration of Conformal ArrayAntenna with Instrumental Sensors Method [A],2008IEEE International Workshopon Antenna Technology: Small Antennas and Novel Metamaterials, Chiba, Japan,2008, pp.406-409, Chiba, Japan,2008, pp.406-409.
[24]I. G. Cumming and F. H. Wong, Digital Processing of Synthetic Aperture RadarData: Algorithms and Implementation [M], Norwood, MA: Artech House,2005.
[25]M. Grant, S. Boyd, and Y. Ye,―cvx: Matlab software for disciplined convexprogramming,‖[online]. Available: http://www.stanford.edu/~boyd/cvx/.
[26]J. S. Sturm, Using SeDuMi1.02, a Matlab Toolbox for Optimization OverSymmetric cones [R], Tech. Rep. Tiburg University, Deparment of Econometrics,Netherlands,2001.
[2] J. P. Fitch. Synthetic Aperture Radar. Springer-Verlag New York Inc.,1988.
[3]张澄波.综合孔径雷达.北京:科学出版社，1989.
[4] J. C. Curlander and R. N. McDonough. Synthetic Aperture Radar: System andSignal Processing. Jone Wiley&Sons, INC,1991.
[5] D. R. Wehner. High-Resolution Radar.2nd Edition. Boston, MA: Artech House,Inc.1994.
[6] W. G. Carrara, R. S. Goodman, and R. M. Majewski, Spotlight Synthetic ApertureRadar: Signal Processing Algorithm [M]. Boston, MA: Artech House,1995.
[7] C. V. Jakowatz Jr., D. E. Wahl, P. H. Eichel, D. C. Ghiglia, and P. A. Thompson.Spotlight-Mode Synthetic Aperture Radar: A Signal Processing Approach, Boston:KluwerAcademic Publishers,1996.
[8] M. Soumekh. Synthetic Aperture Radar Signal Processing with MATLABAlgorithms. John Wiley&Sons, Inc.1999.
[9]刘永坦.雷达成像技术.哈尔滨:哈尔滨工业大学出版社，1999.
[10]G. Franceschetti and R. Lanari. Synthetic Aperture Radar Processing, CRC PressBoca Raton, Mar.30,1999.
[11]R. J. Sullivan. Micowave Radar Imaging and Advanced Concepts. Boston: ArtechHouse,2000.
[12]袁孝康.星载合成孔径雷达导论[M].北京:国防工业出版社,2003.
[13]张直中.机载和星载合成孔径雷达导论[M].北京:电子工业出版社,2004.
[14]保铮,邢孟道,王彤.雷达成像技术[M].北京:电子工业出版社,2005.
[15]Ian G. Cumming, Frank H. Wong著,洪文,胡东辉等译.合成孔径雷达成像—算法与实现[M].北京:电子工业出版社,2007.
[16]M. I. Skolnik.王军等译.雷达手册[M].北京:电子工业出版社,2003.
[17]C. Elahci, T. Bicknell, R. L. Jordan, and C. Wu. Spaceborne Synthetic ApertureImaging Radars: Application, Techniques, and Technology [J]. Proc. of IEEE.1982,70(10).1174-1209.
[18]W. M. Brown. Synthetic Aperture Radar [J], IEEE Trans. on AES,1967,3(2).217-229.
[19] W. M. Brown and L.J. Porcello. An Introduction to Synthetic Aperture Radar [J],IEEE Spectrum, Sept.1969, Vol.6.52-62.
[20]C. A. Wiley. Synthetic Aperture Radars [J]. IEEE Trans. on AES,1985,21(3).440-443.
[21]D. R. Wehner. High-Resolution Radar [M],2nd Edition. Boston, MA: ArtechHouse, Inc.1994.
[22]D. L. Mensa. High Resolution Radar Cross-Section Imaging [M]. Artech House,Inc.1991.
[23]B. Borden. Radar Imaging of Airborne Targets: A Primer for AppliedMathematicians and Physicists [M]. Bristol, Philadelphia: Institute of Physics Pub.,1999.
[24]M. J. Pricket, C. C. Chen. Principle of Inverse Synthetic Aperture Radar(ISAR)Imaging [C]. EASCON record, Arlington, VA, Sep.29-Oct.1,1980.340-345.
[25]W. M. Brown. Synthetic Aperture Radar [J]. IEEE Trans. on AES,1967, Vol.3(2).217-229.
[26]C. W. Sherwin, J. P. Ruina, R. D. Rawcliffe. Some Early Developments inSynthetic Aperture Radar Systems [M], IRE Trans. on Military Electronics,1962,Vol.6(2),111-115.
[27]Elahci C, Bicknell T, Jordan R L, and Wu C. Spaceborne Synthetic ApertureImaging Radars: Application, Techniques, and Technology [J]. Proc. of IEEE,1982,70(10):1174-1209.
[28]http://ilrs.gsfc.nasa.gov/satellite_missions/list_of_satellites/seas_general.html.
[29]http://en.wikipedia.org/wiki/Lacrosse
[30]郭华东,王长林.全天候全天时三维航天遥感技术-介绍航天飞机雷达地形测图计划[J],遥感信息,2000,(1):47-48.
[31]http://www.infoterra.de/terrasar-x-satelliteH.
[32]http://www.dlr.de/hr/en/desktopdefault.aspx/tabid-2326/3776_read-5691/.
[33]http://www.fhr.fraunhofer.de/fhr/fhr_c628_f7_en.html.
[34]R. W. Bayma, E. Trujillo, HISARTM COTS-based synthetic aperture radar [A].Digital Avionics Systems Conference,1996:319-325.
[35]S. I. Tsunoda, F. Pace, J. Stence, M. Woodring, Lynx: A High-resolution SyntheticAperture Radar [A], SPIE Aerosense [C],1999, vol.3704,1-8.
[36]http://www.sandia.gov/radar/minisar.html.
[37]J R Bennett, I G Cumming. A Digital Processor for the Production of SeasatSynthetic Aperture Radar Imagery [A]. Proc. SURGE workshop, Frascati,ESA-SP-154,1979.
[38]J R Bennett, I G Cumming, R A Deane. The Digital Processing of Seasat SyntheticAperture Radar Data [A]. IEEE Inter. Radar conf [C]. Washington:1980.168-175.
[39]Munson D C, Jr. OBrien J D, Jenkins W K. A Tomographic Formation of SpotlightMode Synthetic Aperture Radar [J]. Proc. IEEE,1983,71(8):917-925.
[40]C Cafforio, C Prati, F Rocca. Full Resolution Focusing of SEASAT SAR Images inthe Frequency-wave Number Domain [A]. Proc. of the8th EARSeLSymposium[C]. Capri Italy:1988.336-355.
[41]F Rocca, C Cafforio, C Prati. Synthetic Aperture Radar: A New Application forWave Equation Techniques [J]. Geophysical prospecting,1989,37.809-830.
[42]R K Raney, P W Vachon. A Phase Preserving SAR Processor [A]. IGARSS’89[C].1989.2588-2591.
[43]R K Raney, H Runge, R Bamler, I G Cumming, F H Wong. Precision SARProcessing Using Chirp Scaling [J]. IEEE Trans. on GRS,1994,32(4):786-799.
[44]G W Davidson, I G Cumming, M R Ito. A Chirp Scaling Approach for ProcessingSquint Mode SAR Data [J]. IEEE Trans. on AES,1996,32(1):121-133.
[45]Cantafio L J.(Ed.). Space-based Radar Handbook [M]. Boston, Artech House,1989.
[46]G. Krieger and A. Moreira, Spaceborne Bi-and Multistatic SAR: Potential andChallenges [J], IEE Proceedings–Radar, Sonar and Navigation,2006,153(3), pp.184-198.
[47]G. Krieger, N. Gebert, A. Moreira. Multidimensional Waveform Encoding: A NewDigital Beamforming Technique for Synthetic Aperture Radar Remote Sensing.IEEE Trans. on GRS,2008,46(1):31-46.
[48]N. Gebert, G. Krieger, and A. Moreira, Digital Beamforming on Receive:Techniques and Optimization Strategies for High-Resolution Wide-Swath SARImaging [J], IEEE Trans. on AES,2009,45(2),564-592.
[49]G. Krieger, N. Gebert, A. Moreira. Unambiguous SAR Signal Reconstruction FromNonuniform Displaced Phase Center Sampling [J]. IEEE GRSL,2004,1(4):260:264.
[50]Zhenfang Li, Zheng Bao, Hai Li, Guisheng Liao. Image Auto-Coregistration andInSAR Interferogram Estimation Using Joint Subspace Projection [J]. IEEE Trans.on GRS,2006,44(2):288-297.
[51]Zhenfang Li, Zheng Bao, Hongyang Wang, Guisheng Liao. Performanceimprovement for constellation SAR using signal processing techniques [J]. IEEETrans. on AES,2006,42(2):436-452.
[52]N. Goodman, S. Lin, D. Rajakrishna, and J. Stiles, Processing of Multiple-ReceiverSpaceborne Arrays for Wide-Area SAR [J], IEEE Trans. on GRS,40(4), pp.841-852, Apr.2002.
[53]Wang Tong, Bao Zheng，Zhang Zhenghua, Ding Jingshan. Improving Coherence ofComplex Image Pairs Obtained by Along-Track Bistatic SARs UsingRange–Azimuth Prefiltering [J]. IEEE Trans. on GRS,2008,46(1):3–13.
[54]A. Moreira and H. Yonghong, Airborne SAR Processing of Highly Squinted DataUsing a Chirp Scaling Approach with Integrated Motion Compensation [J], IEEETrans. on GRS,1994,32(5), pp.1029-1040.
[55]C. E. Mancill, and J. M. Swiger, A Map Draft Autofocus Technique for CorrectingHigher Order SAR Phase Errors [A],27th Annual Tri-Service Radar SymposiumRecord, Monterey, CA, pp.391-400, June23-25,1981.
[56]M. Xing, X. Jiang, R. Wu, F. Zhou and Z. Bao, Motion Compensation for UAVSAR Based on Raw Radar Data [J], IEEE Trans. on GRS,2009,47(8),2870-2883.
[57]P. Samczy ski, G. Pietrzyk, and A. Gorzelanczyk, Coherent MapDrift Technique[J], IEEE Trans. on GRS,2010,48(3),1505-1517.
[58]D. E. Wahl, P. H. Eichel, D. C. Ghiglia, and C. V. Jakowatz, Jr., Phase GradientAutofocus—A Robust Tool for High Resolution Phase Correction [J], IEEE Trans.on AES,1994,30(3),827–835.
[59]H. L. Chan and T. S. Yeo, Noniterative Quality Phase-Gradient Autofocus (QPGA)Algrotihm for Spotlight SAR Imagery [J], IEEE Trans. on GRS,1998,36(5),1531-1539.
[60]W. Ye, T. S. Yeo and Z Bao, Weighted Least-Squares Estimation of Phase Errorsfor SAR/ISAR Autofocus [J], IEEE Trans. on GRS,1999,37(5),.2487-2494.
[61]X. Li, G. Liu, J. Ni, Autofocusing of ISAR Images Based on Entropy Minimization[J], IEEE Trans. on AES,1999,35(4),1240-1251.
[62]F. Berizzi, G. Cosini, M. Diani, M. Veltroni, Autofocus of Wide Azimuth AngleSAR Images by Contrast Optimization [A], IEEE Radar Conference,1230-1232,1996.
[63]Ausherman Dale A., Kozma Adam, Walker Jack L., Jones Harrison M., PoggioEnrico C.. Developments in Radar Imaging [J]., IEEE Trans. on AES,1984,20（4）,363-400.
[64]D. A. Ausherman, A. Kozma, J.L. Walker, H.M. et al.. Developments in RadarImaging [J], IEEE Trans. on AES,1984,20(4),363-399.
[65]史仁杰,雷达反导与林肯实验室[J].系统工程与电子技术.2007,29(11),1781-1799.
[66]Herbert G. Weiss, The Millstone and Haystack Radars [J]，IEEE Trans. on AES.2001,37(1),365-379.
[67]MIT Lincoln Laboratory2009Annual Report. www.ll.mit.edu.
[68]A Sourcebook for the Use of the FGAN Tracking and Imaging Radar for SatelliteImaging. http://www.fhr.fgan.de/fhr/fhr_en.html.
[69]C. C. Chen and H. C. Andrews. Target-motion-induced Rader Imaging [J]. IEEETrans. on AES,1980,7(16),2-14.
[70]C. Chen, H. C. Andrews. Multifrequency Imaging of Radar Turntable Data [J],IEEE Trans. on AES,1980,16(1),15-22.
[71]M. Soumekh, S. Nugroho. ISAR Imaging of An Airborne DC-9[A]. Proc ICASSP.1993,465-468.
[72]R. Goodman, W, Nagy, Wilelm. A High Fidelity Ground to Air Imaging RadarSystem [A]. IEEE National Radar Conference Record.1994,29-34.
[73]V. C. Chen, S. Qian. Joint Time-Frequency Transform for Radar Range-DopplerImaging [J]. IEEE Trans. on AES,1998,34(2):486-499.
[74]V. C. Chen. Adaptive Time-Frequency ISAR Processing [C]. SPIE1996, Denver,Co, USA,1996:133-140.
[75]S.L.Borison, S.B.Bowling, and K.M.Cuomo, Super-Resolution Methods forWideband Radar [J], Lincoln Lab. J.,1992,5(3)441-461.
[76]T. G. Moore, B. W. Zuerndorfer, and E. C. Burt, Enhanced Imagery UsingSpectral-Estimation-Based Techniques [J], Lincoln Lab. J.,1997,10(2),171–186.
[77]J. Li and P. Stoica,An Adaptive Filtering Approach to Spectral Estimation and SARImaging [J], IEEE Trans. on SP,1996,44(6),1469-1484.
[78]Li J, Stoica P. Efficient Mixed-Spectrum Estimation with Applications to TargetFeature Extraction [J], IEEE Trans. on SP,1996,44(2),281-295.
[79]Z.S.Liu, J.Li, Synthetic Aperture Radar Motion Compensation and FeatureExtraction by Means of A Relaxation-Based Algorithm [J], J. Opt. Soc. Am. A.,1998,15(3),599-610.
[80]K. M. Cuomo, J. E. Piou, and J. T. Mayhan. Ultrawide-Band Coherent Processing[J]. IEEE Trans. on AP.1999,47(6).1097-1107.
[81]L. D. Vann, K. M. Cuomo, J. E. Piou, Multisensor Fusion Processing for EnhancedRadar Imaging [R], Lincoln Lab., MIT, Technical report1056,2000.
[82]D. Pastina, M Bucciarelli and P Lombardo, Multistatic and MIMO DistributedISAR for Enhanced Cross-Range Resolution of Rotating Targets [J], IEEE Trans.on GRS,2010,48(8),3300-3317.
[83]王成，雷达信号层融合成像技术研究[D]，国防科技大学，长沙：2006.
[84]保铮,王根原,罗琳.逆合成孔径雷达的距离-瞬时多普勒成像方法.电子学报.1998,26(12).79-83.
[85]王根原,保铮.一种基于自适应Chirplet分解的逆合成孔径雷达成像方法.电子学报.1999,27(3).29-31.
[1] Q. Zhang and Y. Q. Jin, Aspects of Radar Imaging Using Frequency-Stepped ChirpSignals [J], EURASIP Joural Applied Signal Processing, Vol.2006,2006,1–8,Article ID85823.
[2] T. G. Moore, B. W. Zuerndorfer and E. C. Burt, Enhanced Imagery UsingSpectral-Estimation-Based Techniques [J], Lincoln Lab. J.,10(2),1997,171–186.
[3] J. T. Mayhan, M. L. Burrows, K. M. Cuomo and J. E. Piou, High Resolution3D―Snapshot‖ISAR Imaging and Feature Extraction [J], IEEE Trans. on AES, April2001,Vol.37(2),630-641.
[4] K. Suwa, Toshio Wakayama, and M. Iwamoto, Three-Dimensional TargetGeometry and Target Motion Estimation Method Using Multistatic ISAR Moviesand Its Performance [J], IEEE Trans. on GRS, Janunary2011,45(1),45–54.
[5] S. L. Borison, S. B. Bowling, and K. M. Cuomo, Super-Resolution Methods forWideband Radar [J], Lincoln Lab. J.,1992,5(3),441–461.
[6] J.Gudnason, J. Cui, M. Brookes, HRR Automatic Target Recognition FromSuperresolution Scattering Center Features [J], IEEE Trans. on AES,2009,45(4),1512-1524.
[7] L. M. Novak, G. J. Owirka, and A. L. Weaver, Automatic Target Recognition UsingEnhanced Resolution SAR Data [J], IEEE Trans. On AES,1999,35(1),157–175.
[8] H. J. Li, N. H. Farhat, and Y. S. Shen, A New Iterative Algorithm for Extrapolationof Data Available in Multiple Restricted Regions with Applications to RadarImaging [J], IEEE Trans. on AP, May1987,35(5),581–588.
[9] K. Suwa, and M. Iwamoto, A Two-Dimensional Bandwidth ExtrapolationTechnique for Polarimetric Synthetic Aperture Radar Images [J], IEEE Trans. onGRS,45(1), Janurary2007,45–54.
[10]I. J. Gupta, High-Resolution Radar Imaging Using2-D Linear Prediction [J], IEEETrans. on AP,42(1), January1994,31–37.
[11]T. G. Moore, B. W. Zuerndorfer, and E. C. Burt, Enhanced Imagery UsingSpectral-Estimation-Based Techniques [J], Lincoln Lab. J.,1997,10(2),171–186.
[12]R. O. Lane, K. D. Copsey, A. R. Webb, A Bayesian Approach to SimultaneousAutofocus and Super-Resolution [J], Proceedings of SPIE, Vol.5427, April2004,133-142.
[13]A. Mohammad-Djafari and G. Demoment, Maximum Entropy Fourier Synthesiswith Application to Diffraction Tomography [J], Appl. Opt., Vol.26,1989,1745-1754.
[14]Li, J., and Stoica, P. Efficient Mixed-Spectrum Estimation with Applications toTarget Feature Extraction [J], IEEE Trans. on SP, February1996,44(2),281-295.
[15]Bi, Z., Li, J., and Liu, Z. S., Super Resolution SAR Imaging Via ParametricSpectral Estimation Methods [J], IEEE Trans. on AES, Janurary1999,35(1),267-281.
[16]A. D. Lazarov, Iterative Minimum Mean Square Error Method and RecurrentKalman Procedure for ISAR Image Reconstruction [J], IEEE Trans. on AES,2001,37(4),1432-1441.
[17]Z. S. Liu, R. Wu, J. Li, Complex ISAR Imaging of Maneuvering Targets Via theCapon Estimator [J], IEEE Trans. on SP,1999,47(5),1262-1271.
[18]M. R. Palsetia and J. Li, Using APES for Interferometric SAR Imaging [J], IEEETrans. on IP,1998,7(9),1340–1353.
[19]Li, J., and Stoica, P., An Adaptive Filtering Approach to Spectral Estimation andSAR Imaging [J], IEEE Trans. on SP,1996,44(2),1469-1484.
[20]H. C. Stankwitz, R. J. Dallaire, and J. R. Fienup, Nonlinear Apodization forSidelobe Control in SAR Imagery [J], IEEE Trans. on AES,1995,31(1),267–279.
[21]X. Xu and R. M. Narayanan, Enhanced Resolution in SAR/ISAR Imaging UsingIterative Sidelobe Apodization [J], IEEE Trans. on IP,2005,14(4),537-547.
[22]J. Tsao, and B. D. Steinberg, Reduction of Sidelobe and Speckle Artifacts inMicrowave Imaging: The CLEAN Technique [J], IEEE Trans. on AP,1988,36(4),1688-1697.
[23]R. Bose, A. Freeman, B. D. Steinberg, Sequence CLEAN: A ModifiedDeconvolution Technique for Microwave Images of Contiguous Targets [J], IEEETrans. on AES,2002,38(1),89-96.
[24]E. Cand`es, J. Romberg, and T. Tao, Robust Uncertainty Principles: Exact SignalReconstruction From Highly Incomplete Frequency Information [J], IEEE Trans.on IT,2006,52(2),489–509.
[25]E. Cand`es, J. Romberg, and T. Tao, Near-Optimal Signal Recovery From RandomProjections: Universal Encoding Strategies?[J], IEEE Trans. on IT,2006,52(2),489–509.
[26]D. Donoho, Compressed Sensing [J], IEEE Trans. on IT,2006,52(4),5406–5425.
[27]Zweig, G., Super-Resolution Fourier Transforms by Optimization and ISARImaging [J], IEE Proc-RSN, Vol.150(4), July2003,247-252.
[28]C. W. Zhu, Stable Recovery of Sparse Signals Via Regularized Minimization [J],IEEE Trans. on IT,2008,54(7),3364–3367.
[29]E. van den Berg and M. P. Friedlander, In Pursuit of A Root [R], Tech. Rep.TR-2007-19, Department of Computer Science, University of British Columbia,June2007, http://www.optimization-online.org/DB_HTML/2007/06/1708.html.
[30]M. etin and W. C. Karl, Feature-Enhanced Synthetic Aperture Radar ImageFormation Based on Nonquadratic Regularization [J], IEEE Trans. on IP,2001,10(4),623-631.
[31]M. etin, Feature-Enhanced Synthetic Aperture Radar Imaging [D], BostonUniversity，Docter Dessertion，2001.
[32]Joachim H.G. Ender,On Compressive Sensing Applied to Radar [J], SignalProcessing,2010,90(5),1402-1414.
[33]Matthew A. Herman, Thomas Strohmer. High-Resolution Radar via CompressedSensing [J]. IEEE Trans. on SP,2009,57(6),2275-2284.
[34]X. X. Zhu, R. Bamler, Tomographic SAR Inversion By l1-norm Regularization-TheCompressive Sensing Approach [J], IEEE Trans. on GRS,2009,48(10),3839-3846.
[35]Alessandra Budillon, Annarita Evangelista, and Gilda Schirinzi, Three-DimensionalSAR Focusing From Multipass Signals Using Compressive Sampling [J], IEEE.Trans. on GRS,2011,49(1),488–499.
[36]Y. Wang, H. Ling, V. C. Chen, ISAR Motion Compensation via Adaptive JointTime-Frequency Techniques [J], IEEE Trans. on AES,1998,34(2),670-677.
[37]W. Ye, T. S. Yeo, and Z. Bao, Weighted Least Squares Estimation of Phase Errorsfor SAR/ISAR Autofocus [J], IEEE Trans. on GRS,1999,37(5).2487-2494.
[38]J. Wang and D. Kasilingam, Global Range Alignment for ISAR [J], IEEE Trans. onAES,2003,39(1),351–357.
[39]T. Sauer and A. Schroth, Robust Range Alignment Algorithm Via Hough Transformin An ISAR Imaging System [J], IEEE Trans. on AES,1995,31(3),1173–1177.
[40]D. Zhu, L. Wang, Y. Yu, Q. Tao, and Z. Zhu, Robust ISAR Range Alignment ViaMinimizing the Entropy of the Average Range Profile [J], IEEE GRSL,2009,6(2),204-208.
[41]Q. Zhang, T. S. Yeo, Estimation of Three-Dimensional Motion Parameters inInterferometric ISAR Imaging [J], IEEE Trans. on GRS,2004,42,292-300.
[42]T. Thayaparan, L. Stankovic, C. Wernik, and M. Dakovic, Real-Time MotionCompensation, Image Formation and Image Enhancement of Moving Targets inISAR and SAR Using S-method Based Approach [J], IET Signal Processing,2008,2(3),247-264.
[43]保铮,邢孟道,王彤.雷达成像技术[M].北京：电子工业出版社。
[44]L. Zhang, M. D. Xing, C.W. Qiu, J. Li, Z. Bao, Achieving Higher Resolution ISARImaging with Limited Pulses via Compressed Sampling [J], IEEE GRSL,2009,6(3),567-571.
[45]M. Grant, S. Boyd, and Y. Ye, cvx: Matlab Software for Disciplined ConvexProgramming [R],[online]. Available: http://www.stanford.edu/~boyd/cvx/.
[46]S. Chen, D. Donoho, and M.A. Saunders, Atomic Decomposition by Basis Pursuit[J], SIAM J. Sci Comp.,1999,20(1),33–61.
[47]Thomas Blumensath and Mike E. Davies, Gradient Pursuits [J], IEEE Trans. on SP,2008,56(6),2370-2382.
[48]Tropp, J.A.; Gilbert, A.C. Signal Recovery from Random Measurements ViaOrthogonal Matching Pursuit [J], IEEE Trans. on IT,2007,53(12),4655-4666.
[49]L. Applebaum, S. Howard, S. Searle, and R. Calderbank, Chirp Sensing Codes:Deterministic Compressed Sensing Measurements for Fast Recovery [J], Appl.Comput. Harmonic Anal.,2008,26(2),283-290.
[50]E. Candès, J. Romberg, and T. Tao, Stable Signal Recovery From Incomplete andInaccurate Measurements [J], Comm. Pure Appl. Math,2006,59(8),1027-1223,.
[51]L. Zhang, M. D. Xing, C.W. Qiu, J. Li, J. Sheng, Y. Li, Z. Bao, ResolutionEnhancement for Inversed Synthetic Aperture Radar Imaging under Low SNR viaImproved Compressive Sensing [J], IEEE Trans. on GRS,2010,48(10),3824-3838,.
[52]S. Ji, Y. Xue and L. Carin, Bayesian Compressive Sensing [J], IEEE Trans. on SP,2008,56(6),2346–2356.
[53]S.D. Babacan, R. Molina, and A.K. Katsaggelos, Bayesian Compressive SensingUsing Laplace Priors [J], IEEE Trans. on IP,2010,19(1),53–63.
[54]E. van den Berg and M. P. Friedlander, In pursuit of a root [R], Tech. Rep.TR-2007-19, Department of Computer Science, University of British Columbia,June2007,: http://www.optimization-online.org/DB_HTML/2007/06/1708.html
[55]E. Candès, and M. Wakin, B., Enhancing Sparsity by Reweighted l1Minimization[J], Journal of Fourier Analysis and Applications special issue on sparsity,December2008,14(5),877-905,.
[56]H. Rohling, Radar CFAR Thresholding in Clutter and Multiple Target Situations [J],IEEE Trans. on AES,1983,19,608-621.
[57]G. Davidson, Radar toolbox, Available: http://www.radarworks.com/software.htm.
[58]P. R. Wu, A Criterion for Radar Resolution Enhancement with Burg Algorithm [J],IEEE Trans. on AES,1995,31(2),877-915.
[59]J. F. Sturm. Using SeDuMi1.02, a Matlab toolbox for optimization over symmetriccones. Technical report, Department of Econometrics, Tilburg University, Tilburg,The Netherlands, August1998–October2001.
[60]D. L. Donoho ect.. Sparselab. http://sparselab.stanford.edu/,2007.
[61]Y. Zhang,―YALL1,‖http://www.caam.rice.edu/~optimization/L1/YALL1/.
[62]C. R. Vogel and M. E. Oman, Fast, Robust Total Variation-Based Reconstruction ofNoisy, Blurred Images [J], IEEE Trans. on IP, Vol.7,1998, pp.813–824.
[63]L. Du, H. W. Liu, Z. Bao and M. Xing, Radar HRRP Target Recognition Based onHigher-Order Spectra [J], IEEE Trans. on SP,2005,53(7),2359-2368.
[64]G. Yu, and G. Sapiro, Statistical Compressive Sensing of Gaussian Mixture Models[J], http://arxiv.org/abs/1010.4314,2010.
[1] S. L. Borison, S. B. Bowling, and K. M. Cuomo, Super-Resolution Methods forWideband Radar[J], Lincoln Lab. J.,1992,5(3),441–461.
[2] Q. Zhang and Y. Q. Jin, Aspects of Radar Imaging Using Frequency-Stepped ChirpSignals [J], EURASIP J. Appl. Signal Process.,2006,1–8, Article ID85823.
[3] G. S. Gill, Step Frequency Waveform Design and Processing for Detection ofMoving Targets in Clutter [A], in Proc. IEEE Int. Radar Conf., May8–11,1995,573–578.
[4] R. Barvainis, J.A. Ball, R.P. Ingalls, and J.E. Salah. The Haystack Observatoryλ3-mm Upgrade. Publ.Astron. Soc. Pac.1993,105(693),1334–1341.
[5] Technology in Support of National Security [R]. MIT Lincoln Laboratory Report2010,12-13.
[6] A. Freedman, R. Bose, and B. D. Steinberg, Thinned Stepped FrequencyWaveforms to Furnish Existing Radars with Imaging Capability [J], IEEE Aerosp.Electron. Syst. Mag.,1996,11(11),39–43.
[7] A. Freedman, R. Bose, and B. D. Steinberg, Thinned Stepped FrequencyWaveforms to Furnish Existing Radars with Imaging Capability [J], IEEE AESMagazine,1996,11(11),39–43.
[8] R. Bose, A. Freeman and B. D. Steinberg, Sequence CLEAN: A ModifiedDeconvolution Technique for Microwave Images of Contiguous Targets [J], IEEETrans. on AES,2002,38(1),89-96.
[9] H. J. Li, N. H. Farhat, and Y. S. Shen, A New Iterative Algorithm for Extrapolationof Data Available in Multiple Restricted Regions with Applications to RadarImaging [J], IEEE Trans. on AP,1987,35(5),581–588.
[10] K. Suwa, and M. Iwamoto, A Two-Dimensional Bandwidth ExtrapolationTechnique for Polarimetric Synthetic Aperture Radar Images [J], IEEE Trans. onGRS,2007,45(1),45–54.
[11] I. J. Gupta, High-resolution radar imaging using2-D linear prediction [J], IEEETrans. on AP,1994,42(1),31–37.
[12] T. G. Moore, B. W. Zuerndorfer and E. C. Burt, Enhanced Imagery UsingSpectral-Estimation-Based Techniques [J], Lincoln Lab. J.,1997,10(2),171–186.
[13] S. L. Borison, S. B. Bowling, and K. M. Cuomo, Super-resolution methods forwideband radar [J], Lincoln Lab. J.,1992,5(3),441–461.
[14] K. M. Cuomo, J. E. Piou, and J. T. Mayhan, Ultrawide-Band Coherent Processing[J], IEEE Trans. on AP.1999,47(6),1097-1107.
[15] Li, J., and Stoica, P. Efficient Mixed-Spectrum Estimation with Applications toTarget Feature Extraction [J], IEEE Trans. on SP,1996,44(2):281-295.
[16] Bi, Z., Li, J., and Liu, Z.-S. Super Resolution SAR Imaging via ParametricSpectral Estimation Methods [J]. IEEE Trans. on AES,1999,35(1):267-281.
[17] Z. S. Liu, R. Wu, J. Li: Complex ISAR Imaging of Maneuvering Targets via theCapon Estimator [J], IEEE Trans. on SP,1999,47(5),1262-1271.
[18] E. G. Larsson, P. Stoica, J. Li, Amplitude Spectrum Estimation forTwo-Dimensional Gapped Data [J], IEEE Trans. on SP,2002,50(6),1343-1353.
[19] M. Cetin and R. L. Moses. SAR Imaging from Partial-Aperture Data withFrequency-Band Omissions [C]. SPIE Defense and Security Symposium,Algorithm for Synthetic Aperture Radar Imaging Ⅻ, Orlando, Florida, March2005.
[20] M. Cetin and W. C. Karl. Feature-Enhanced Synthetic Aperture Radar ImageFormation Based on Nonquadratic Regularization [J]. IEEE Trans. on IP.2001,10(4),623-631.
[21] Joachim H.G. Ender, On Compressive Sensing Applied to Radar [J], SignalProcessing,2010,90(5),1402-1414.
[22] E. Candès, J. Romberg, and T. Tao, Robust Uncertainty Principles: Exact SignalReconstruction from Highly Incomplete Frequency Information [J], IEEE Trans.on IT,52(2),489–509,2006.
[23] E. Candès, J. Romberg, and T. Tao, Near-Optimal Signal Recovery From RandomProjections: Universal Encoding Strategies?[J], IEEE Trans. on IT,2006,52(2),489–509.
[24] D. Donoho, Compressed Sensing [J], IEEE Trans. on IT, April2006,52(4),5406–5425.
[25] L. Zhang, M. Xing, C. Qiu, J. Li and Z. Bao., Achieving Higher Resolution ISARImaging with Limited Pulses via Compressed Sampling [J], IEEE. GRSL,2009,6(3),567-571.
[26] K. R. Varshney, M. etin, J. W. Fisher and A. S. Willsky, Sparse Representation inStructured Dictionaries with Application to Synthetic Aperture Radar [J], IEEETrans. on SP,2008,56(8),3548-3561.
[27] A. C. Gurbuz, J. H. McClellan and W.R. Scott, A Compressive Sensing DataAcquisition and Imaging Method for Stepped Frequency GPRs [J], IEEE Trans. onSP,2009,57(7),2640-2650.
[28] X. Zhu, R. Bamler, Tomographic SAR Inversion by L1-norm Regularization-theCompressive Sensing Approach [J], IEEE Trams on GRS,2010,48(10),3839-3846.
[29] S. Ji, Y. Xue and L. Carin, Bayesian Compressive Sensing [J], IEEE Trans. on SP,2008,56(6),2346–2356.
[30] F. Berizzi, M. Martorella, A. Cacciamano, and A. Capria, A Contrast-basedAlgorithm for Synthetic Range-Profile Motion Compensation [J], IEEE Trans. onGRS,2008,46(10),3053–3062.
[31] H. Chen, Y. Liu, W. Jiang, and G.. Guo, A New Approach for Synthesizing theRange Profile of Moving Targets via Stepped-Frequency Waveforms [J], IEEEGRSL,2006,3(3),406–409.
[32] H. Rohling, Radar CFAR Thresholding in Clutter and Multiple Target Situations[J], IEEE Trans. on AES,1983,19,608-621.
[33] G. Davidson, Radar toolbox, Available: http://www.radarworks.com/software.htm.
[34] S.P. Boyd and L. Vandenberghe. Convex Optimization [M]. Cambridge UniversityPress,2004.
[35] O. Axelsson, Iterative Solution Methods [M], Cambridge University Press,1994.
[36] Y. Wang, H. Ling., and V. C. Chen, ISAR Motion Compensation via AdaptiveJoint Time-Frequency Techniques [M], IEEE Trans. on AES,1998,34(2),670-677.
[37] J. Wang and D. Kasilingam, Global Range Alignment for ISAR [J], IEEE Trans.on AES,2003,39(1),351–357.
[38] D. Zhu, L. Wang, Y. Yu, Q. Tao, and Z. Zhu, Robust ISAR Range Alignment viaMinimizing the Entropy of the Average Range Profile [J], IEEE GRSL,2009,6(2),204-208.
[39] W. Ye, T. S. Yeo, and Z. Bao, Weighted Least-Squares Estimation of Phase Errorsfor SAR/ISAR Autofocus [J], IEEE Trans. on GRS, September.1999, Vol.37(5),2487-2494.
[40] D. E. Wahl, P. H. Eichel, D. C. Chiglia,et al. Phase Gradient Autofocus—a RobustTool for High Resolution SAR Phase Correction [J], IEEE Trans. on AES,1994,30(3),827-834.
[41] Berizzi, and Cosini, G. Autofocusing of Inverse Synthetic Aperture Radar ImagesUsing Contrast Optimization [J], IEEE Trans. on AES, July1996,32(3),1185-1191.
[42] X. Li, G. S. Liu, J. L. Ni, Autofocusing of ISAR Images Based on EntropyMinimization [J], IEEE Trans. on AES, October1999,35(4),1240-1251.
[43] Y. Li, M. Xing, L. Zhang and Z. Bao, Detection, Parameter Estimation andImaging of Maneuvering Target in Wide-band Signal [J], Sci. China Ser. F-Inf Sci.,2009,52(6),1015-1026.
[44] S. Zhu, G. Liao, Y. Qu, X. Liu, and Z. Zhou, A New Slant-Range VelocityAmbiguity Resolving Approach of Fast Moving Targets for SAR System [J], IEEETrans. on GRS,2010,48(1).
[45] G. Y. Wang, X. G. Xia, V. C. Chen, Radar Imaging of Moving Targets in FoliageUsing Multifrequency Multiaperture Polarimetric SAR [J], IEEE Trans. on GRS,2003,41(8),1755-1764.
[46] G. Wang, X. Xia, V. C. Chen and R. L. Fiedler, Detection, Location, and Imagingof Fast Moving Targets Using Multifrequency Antenna Array SAR [J], IEEE Trans.on AES,2004,40(1),345-354.
[47]王琦，空间目标ISAR成像的研究[D]，西安：西安电子科技大学，2007.
[48]臧博，张磊，唐禹，邢孟道，逆合成孔径成像激光雷达低信噪比稀疏多孔径成像方法研究[J]，电子与信息学报，2010，32(12),2808-2813.
[49] K. M. Cuomo, J. E. Piou, and J. T. Mayhan. Ultrawide-Band Coherent Processing[J]. IEEE Trans. on AP.1999,47(6).1097-1107.
[50] D. Pastina, M Bucciarelli and P Lombardo,Multistatic and MIMO DistributedISAR for Enhanced Cross-Range Resolution of Rotating Targets [J], IEEE Trans.on GRS,2010,48(8),3300-3317.
[51]王成，雷达信号层融合成像技术研究[D]，国防科技大学，长沙：2006.
[1] W. G. Carrara, R. S. Goodman, and R. M. Majewski, Spotlight Synthetic ApertureRadar: Signal Processing Algorithm [M]. Boston, MA: Artech House,1995.
[2] G. Fornaro, Trajectory Deviations in Airborne SAR: Analysis and Compensation [J],IEEE Trans. on AES,1999,35(3),997-1009.
[3] A. Moreira and H. Yonghong, Airborne SAR Processing of Highly Squinted DataUsing a Chirp Scaling Approach with Integrated Motion Compensation [J], IEEETrans. on GRS,1994,32(5),1029-1040.
[4] M. Xing, X. Jiang, R. Wu, F. Zhou and Z. Bao, Motion Compensation for UAVSAR Based on Raw Radar Data [J], IEEE Trans. on GRS,2009,47(8),2870-2883.
[5] G. Fornaro, G. Franceschetti, and S. Perna, On Center-Beam Approximation inSAR Motion Compensation [J], IEEE Trans. on GRS,2006,3(2),276–280.
[6] M. Y. Lin and C. Wu, A SAR Correlation Algorithm Which Accommodates LargeRange Migration [J], IEEE Trans. on GRS, November,1984, Vol.22,592–597.
[7] J. L. Walker, Range-Doppler Imaging of Rotating Objects [J], IEEE Trans. on AES,1980,16(1),670-677.
[8] I. Cumming, F. Wang, Digital Processing of Synthetic Aperture Radar Data:Algorithm and Implementation [M], Norwood, MA: Artech House,2005.
[9] R. K. Raney, H. Runge, R. Bamler, I. G. Cumming, and F. H. Wong, Precision SARProcessing Using Chirp Scaling [J], IEEE Trans. on GRS,1994,32(4),786–799.
[10] F. Wong, I. Cumming, and R. K. Ranley, Processing Simulated RADARSAT SARData with Squint by a High Precision Algorithm [A], Proc. IEEE Geosci. RemoteSensing Symp.,1176–1178,1993.
[11] G. W. Davidson, A Chirp Scaling Approach for Processing High Squint ModeSAR Data [J], IEEE Trans. on AES,1996,32(1):121–133.
[12] J. Mittermayer, A. Moreira, and O. Loffeld, Spotlight SAR data processing usingthe frequency scaling algorithm [J], IEEE Trans. on GRS,1999,37(4):2198–2214.
[13] J. Mittermayer, A. Moreira, and O. Loffeld, Spotlight SAR Data Processing Usingthe Frequency Scaling Algorithm [J], IEEE Trans. on GRS,1999,37(5):2198–2214.
[14] D. E. Wahl, P. H. Eichel, D. C. Ghiglia and C. V. Jakowatz, Phase GradientAutofocus—A Robust Tool for High Resolution Phase Correction [J], IEEE Trans.on AES,1994,30(3):827–835.
[15] K. A. C. de Macedo, R. Scheiber and A Moreira, An Autofocus Approach forResidual Motion Errors with Application to Airborne Repeated-pass SARInterferometry [J], IEEE Trans. on GRS,2008,46(10):3151-3162.
[16] H. L. Chan and T. S. Yeo, Noniterative Quality Phase Gradient Autofocus (QPGA)Algrotihm for Spotlight SAR Imagery [J], IEEE Trans. on GRS,1998,36(5):1531-1539.
[17] W. Ye, T. S. Yeo and Z Bao, Weighted Least-Squares Estimation of Phase Errors forSAR/ISAR Autofocus [J], IEEE Trans. on GRS,1999,37(5):2487-2494.
[18] J. H. Callow, Signal Processing for Synthetic Aperture Sonar Image Enhancement
[D], New Zealand, Chirstchurch: Canterbury University,2003.
[19] D. E. Wahl, C. V. Jakowatz, Jr. P. A. Thompson, and D. C. Ghiglia, New Approachto Strip-Map SAR Autofocus [A], in Proc.6thIEEE Digital Signal Process.Workshop, Yosemite National Park, CA,1994:53-56.
[20] M. P. Hayes, H. J. Callow, and P. T. Gough, Stripmap Phase Gradient Autofocus
[C], in Proc. OCEANS, September,22–26,2003,52414–2421.
[21] P. T. Gough, M. P. Hayes, and D. R. Griffiths, Strip-map Path Correction UsingPhase Matching Autofocus [A], in Proc.5thECUA, Lyon, France, July,2000:412-418.
[22] S. N. Madsen, Estimating the Doppler Centriod of SAR Data [J], IEEE Trans. onAES,1989,25(2),134-140.
[23] F. H. Wang and I. G. Cumming, A Combined SAR Doppler Centroid EstimationScheme Based upon Signal Phase [J], IEEE Trans. on GRS,1996,34(3),696–707.
[24] I. G. Cumming, A Spatially Selective Approach to Doppler Estimation forFrame-Based Satellite SAR Processing [J], IEEE Trans. on GRS,1996,42(6),1135-1148.
[25] D. G. Thompson, J. S. Bates, D. V. Arnold, and D. G. Long, Extending the phasegradient autofocus algorithm for low-altitude stripmap mode SAR [A], in ProcIGARSS, Hamburg, Germany, July1999:564-566.
[26] J Moreira, Estimating the Residual Error of the Reflectivity Displacement Methodfor Aircraft Motion Error Extraction from SAR Raw Data [A], Record of the IEEE1990International Radar Conference.1990:70-75.
[27] P. Prats, A. Reigber, and J. J. Mallorqui, Topography-Dependent MotionCompensation for Repeat-pass Interferometric SAR Systems [J], IEEE GRSL,2005,2(2),206–210.
[28] K. A. C. de Macedo and R. Scheiber, Precise Topography-and Aperture DependentMotion Compensation for Airborne SAR [J], IEEE GRSL,2005,2(2),172–176.
[29] R. Scheiber and V. Bothale, Interferometric Multi-Look Techniques for SAR Data[A], in Proc. IEEE IGARSS, Toronto, ON, Canada, June,24–28,2002,1,173–175.
[30] N. Ahmed, T. Natarajan, and K. R. Rao, On Image Processing and a DiscreteCosine Transform [J], IEEE Trans. on Comput.,1974， C-23(1),90–93,.
[31] S. Mallat, A Theory for Multiresolution Signal Decomposition: The WaveletRepresentation [J], IEEE Trans. on PAMI, July1989, Vol.11(7):674–693.
[32] D. L. Donoho and I. M. Johnstone, Adapting to Unknown Smoothness via WaveletShrinkage [J], J. Amer. Statist. Assoc.,1995,90:1200–1224.
[33]黄源宝，机载合成孔径雷达成像算法及运动补偿的研究[D]，西安：西安电子科技大学，2005.
[34] F. H. Wong and T. S. Yeo, New Applications of Non-Linear Chirp Scaling in SARData Processing [J], IEEE Trans. on GRS,2001,39(5):946-953.
[35] T. S. Yeo, N. L. Tan, C. B. Zhang and Y. H. Lu, A New Subaperture Approach toHigh Squint SAR Processing [J], IEEE Trans. on GRS,2001,39(5):954-968.
[36]保铮，邢孟道，王彤，雷达成像技术[M]，北京：电子工业出版社，2005.
[37] G. Franceschetti and R. Lanari, Synthetic Aperture Radar Processing [M]. BocaRaton, FL: CRC Press,1999.
[38] P. Samczy ski, G. Pietrzyk, and A. Gorzelanczyk, Coherent MapDrift technique [J],IEEE Trans. on GRS,2010,48(3):1505-1517.
[1] Zhenfang Li, Zheng Bao, Hongyang Wang and Guisheng Liao, PerformanceImprovement for Constellation SAR Using Signal Processing Techniques [J], IEEETrans. on AES,2006,42(2),436-452.
[2]李真芳,保铮,分布式小卫星SAR系统地面运动目标检测方法[J],电子学报,2005,33(9),1664-1666.
[3] Gerhard Krieger, Nicolas Gebert and Alberto Moreira, Unambiguous SAR SignalReconstruction From Nonuniform Displaced Phase Center Sampling [J], IEEEGRSL,2004,1(4),260-264.
[4] A. Currie and M. A. Brown, Wide-swath SAR [J], IEE Proc. Inst. Elect. Eng. F.,1992,139(2),122-135.
[5] G. D. Callaghan and I. D. Longstaff, Wide Swath Spaceborne SAR Using a QuadElement Aray [J], IEE Proc. RSN, June1999,146(3),159-165.
[6] N. A. Goodman, S. C. Lin, D. Rajakrishna and J. M. Stiles, Processing of MultipleReceiver, Spaceborne Arrays for Wide-Area SAR, IEEE Trans. on GRS,2002,40(4),841-852.
[7]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，2006.
[8] Zhenfang Li, Hongyan Wang, Zheng Bao, Generation of Wide-Swath andHigh-Resolution SAR Images From Multichannel Small Spaceborne SAR System[J], IEEE GRSL,2005,2(1),82-86.
[9] Kim J., Younis M., Becker D., Wiesbeck W., Experimental Performance Analysis ofDigital Beamforming on Synthetic Aperture Radar [A], in7th European Conferenceon Synthetic Aperture Radar, CD-ROM, Friedrichshafen, Germany, June2008.
[10]张贤达，现代信号处理[M]，北京：清华大学出版社，2005.
[11]井伟，星载SAR宽场景高分辨成像技术研究[D]，西安：西安电子科技大学，2008.
[12]J. Li, P. Stoica, Robust Adaptive Beamforming [M], John Wiley&Sons, Inc.,Hoboken, New Jersey,2006.
[13]Sergiy A. Vorobyov, Alex B. Gershman, and Zhi-Quan Luo, Robust AdaptiveBeamforming Using Worst-Case Performance Optimization: A Solution to theSignal Mismatch Problem [J], IEEE Trans. on SP,2003,51(2),313-324.
[14]J. Li, P. Stoica and Z. Wang, On Robust Capon Beamforming and DiagonalLoading [J], IEEE Trans. on SP,2003,51(7),1702-1715.
[15]P. Stoica, Z. Wang and J. Li, Robust Capon Beamforming [J], IEEE SPL,2003,10(6),172-175.
[16]J. Li, P. Stoica and Z. Wang, Doubly Constrained Robust Capon Beamformer [J],IEEE Trans. on SP,2004,52(9),2407-2423.
[17]Niolas Gebert, Gerhard Krigeger, Alberto Moreira, Digital Beamforming onReceive: Techniques and Optimization Strategies for High-Resolution Wide-SwathSAR Imaging [J], IEEE Trans. on AES,2009,45(2),564-592.
[18]L. Ma, Z. Li and S. Liao, System Error Analysis and Calibration Methods ForMulti-Channel SAR [A], Progress In Electromagnetics Research, Vol.112,309-327,2011
[19]Nicolas Gebert, Felipe Queiroz de Almeida, Gerhard Krieger, AdvancedMulti-Channel SAR Imaging–Measured Data Demonstration [A], In: Proceedingsof the International Radar Symposium (IRS), Seiten525-529,2009-09-09,Hamburg, Germany.
[20]Friedlander B.，A Subspace Method for Space Time Adaptive Processing [J], IEEETrans. on SP,2005, Vol.53(1),74-82.
[21]王永良，陈辉，彭应宁，万群，空间谱估计理论与算法[M]，北京：清华大学出版社，2004.
[22]L. Zhang, M. Xing, C. Qiu and Z. Bao, Adaptive Two-step Calibration forHigh-Resolution and Wide-swath SAR imaging [J], IET Radar Sonar Navig.,2010,4(4),548-559.
[23]Wang, B. H., Guo. Y., Mutual Coupling Auto-Calibration of Conformal ArrayAntenna with Instrumental Sensors Method [A],2008IEEE International Workshopon Antenna Technology: Small Antennas and Novel Metamaterials, Chiba, Japan,2008, pp.406-409, Chiba, Japan,2008, pp.406-409.
[24]I. G. Cumming and F. H. Wong, Digital Processing of Synthetic Aperture RadarData: Algorithms and Implementation [M], Norwood, MA: Artech House,2005.
[25]M. Grant, S. Boyd, and Y. Ye,―cvx: Matlab software for disciplined convexprogramming,‖[online]. Available: http://www.stanford.edu/~boyd/cvx/.
[26]J. S. Sturm, Using SeDuMi1.02, a Matlab Toolbox for Optimization OverSymmetric cones [R], Tech. Rep. Tiburg University, Deparment of Econometrics,Netherlands,2001.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |