方位多相位中心SAR高分辨率宽测绘带成像技术研究
发布时间：2018-09-14 11:04
【摘要】：合成孔径雷达(SAR)以其全天候、全天时获取高分辨二维地表图像的能力已经成为一种不可或缺的空间对地遥感手段,无论是在灾害监测、海洋测绘等民用领域还是在广域侦察、舰船检测等军事领域,都受到了高度的的重视并得到了广泛的应用。受制于系统固有约束,常规星载SAR系统不能满足现代空间对地观测任务所提出的连续高分辨率宽测绘带(HRWS)成像需求。采用沿航向分布的多通道接收,方位多相位中心(AMPC)SAR系统能够在低脉冲重复频率(PRF)工作条件下获得方位向的高分辨率,从而实现连续HRWS成像。立足于HRWS成像应用需求,围绕AMPC SAR数据处理与系统性能分析难点,对信号建模与重建、系统性能分析、阵列误差建模与校正以及AMPC SAR模式拓展等关键技术展开研究,主要内容与创新点总结如下:第二章对AMPC SAR内在原理与信号模型进行阐述。通过对品质因子与最小天线面积的分析,揭示出AMPC SAR系统的本质在于通过对传统单天线阵面进行重新配置并结合方位向数字波束形成(DBF)技术实现HRWS观测,付出的代价是系统灵敏度的损失,但是并未克服最小天线面积约束。通过对空间采样特性的分析,给出了广义上的均匀采样PRF表达式,并给出了基于DPCA方法重建后的等效PRF表达式。第三章对AMPC SAR信号重建与性能分析两方面问题展开研究。囿于信号模型的局限,常规信号重建方法只能对宽度为整数倍PRF的杂波谱进行重建,从而导致重建性能在特殊PRF条件下的极度恶化,进而对系统参数设计提出了严格的要求。本文建立了修正回波谱模型,将重建信号带宽这一重要处理参数扩展至任意值而非局限于整数倍的PRF,显著提升常规信号重建方法的稳健性,显著提高了系统参数设计的自由度。基于修正回波谱模型建立了AMPC SAR信号重建的统一DBF处理框架,在此框架下对一系列信号重建方法的重建性能进行分析与比较,从而为信号重建方法优选与系统参数设计提供有力支撑。第四章对阵列误差建模与校正问题展开研究。将通道响应误差与相位中心位置误差统一建模为阵列的沿航位置误差、幅度误差和相位误差,指出相位中心位置误差将引入较大的相位误差,而该相位误差又与下视角紧密相关,从而呈现出空变特性。基于杂波功率谱的衰减特性,提出了一种新的阵列误差估计方法,该方法将杂波谱两侧区间的功率与杂波谱中心区间的功率的比值作为优化目标,得到了稳健的误差估计性能。提出修正正交子空间方法,可在通道数较少条件下也能基于信号子空间与噪声子空间的正交性获得稳健的误差估计性能。提出基于阵列误差模型的相位误差拟合方法,可实现对AMPC SAR数据中存在的空变性相位误差进行快速估计与高精度校正。第五章对基于AMPC体制的双指向SAR(BiDi-SAR)成像技术展开研究。单通道BiDi-SAR对系统PRF有着严苛的要求。本文提出AMPC BiDi-SAR观测模式,并提出了基于LS算法的频谱分离方法,可显著降低系统对PRF的严苛要求,显著提高了BiDi-SAR系统观测能力与系统设计自由度。仿真实验与实测数据处理结果验证了相关理论分析的正确性以及本文所提信号处理方法的有效性,从而为面向HRWS应用的AMPC SAR系统参数设计与实测数据处理提供有力支撑。
[Abstract]:Synthetic Aperture Radar (SAR) has become an indispensable means of space-to-ground remote sensing because of its ability to acquire high-resolution two-dimensional surface images all-weather and all-time. It has been highly valued and widely used in civil areas such as disaster monitoring, marine surveying and mapping, wide-area reconnaissance, ship detection and other military fields. Constrained by the inherent constraints of the system, conventional spaceborne SAR systems can not meet the requirements of continuous high resolution and wide mapping band (HRWS) imaging proposed by modern space-to-Earth observation missions. With multi-channel reception along the course distribution, the azimuth multi-phase center (AMPC) SAR system can obtain a square under low pulse repetition rate (PRF) operating conditions. Based on the requirement of HRWS imaging application, the key technologies of signal modeling and reconstruction, system performance analysis, array error modeling and calibration, and AMPC SAR mode expansion are studied around the difficulties of data processing and system performance analysis of AMPC SAR. In the second chapter, the intrinsic principle and signal model of AMPC SAR are described. By analyzing the quality factor and the minimum antenna area, it is revealed that the essence of AMPC SAR system is to reconfigure the traditional single antenna array and realize the HRWS observation by combining the azimuth digital beamforming (DBF) technology. The cost is the sensitivity of the system. By analyzing the characteristics of spatial sampling, the generalized uniform sampling PRF expression is given, and the equivalent PRF expression based on DPCA reconstruction is given. In the third chapter, the problems of AMPC SAR signal reconstruction and performance analysis are studied. The conventional signal reconstruction method can only reconstruct the clutter spectrum whose width is integer times of PRF, which leads to the extreme deterioration of the reconstructed performance under special PRF conditions. Therefore, strict requirements are put forward for the system parameter design. A modified echo spectrum model is established to extend the reconstructed signal bandwidth to arbitrary values rather than local. Limited to integer multiple PRF, the robustness of conventional signal reconstruction methods is improved and the degree of freedom of system parameter design is improved significantly. A unified DBF processing framework for AMPC SAR signal reconstruction is established based on modified echo spectrum model. Under this framework, the reconstruction performance of a series of signal reconstruction methods is analyzed and compared, so as to achieve signal weight. In Chapter 4, the modeling and correction of array errors are studied. The channel response error and the phase center position error are modeled as the yaw position error, amplitude error and phase error of the array. It is pointed out that the phase center position error will lead to larger phase error. Based on the attenuation characteristics of clutter power spectrum, a new array error estimation method is proposed, which takes the ratio of the power at both sides of the clutter spectrum to the power at the center of the clutter spectrum as the optimization objective and obtains robust error estimation performance. The modified orthogonal subspace method can obtain robust error estimation performance based on the orthogonality of signal subspace and noise subspace under the condition of fewer channels. A phase error fitting method based on array error model is proposed to estimate the spatially varying phase errors in AMPC SAR data quickly and accurately. Chapter 5 is devoted to the study of dual-directional SAR (BiDi-SAR) imaging technology based on AMPC. Single-channel BiDi-SAR has strict requirements for PRF. In this paper, AMPC BiDi-SAR observation mode is proposed, and a spectrum separation method based on LS algorithm is proposed, which can significantly reduce the severe requirements of PRF and significantly improve the observation of BiDi-SAR system. The simulation and experimental data processing results verify the correctness of the relevant theoretical analysis and the validity of the signal processing method proposed in this paper, thus providing a strong support for HRWS-oriented AMPC SAR system parameter design and real-time data processing.
【学位授予单位】：国防科学技术大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN958
本文编号：2242519
[Abstract]:Synthetic Aperture Radar (SAR) has become an indispensable means of space-to-ground remote sensing because of its ability to acquire high-resolution two-dimensional surface images all-weather and all-time. It has been highly valued and widely used in civil areas such as disaster monitoring, marine surveying and mapping, wide-area reconnaissance, ship detection and other military fields. Constrained by the inherent constraints of the system, conventional spaceborne SAR systems can not meet the requirements of continuous high resolution and wide mapping band (HRWS) imaging proposed by modern space-to-Earth observation missions. With multi-channel reception along the course distribution, the azimuth multi-phase center (AMPC) SAR system can obtain a square under low pulse repetition rate (PRF) operating conditions. Based on the requirement of HRWS imaging application, the key technologies of signal modeling and reconstruction, system performance analysis, array error modeling and calibration, and AMPC SAR mode expansion are studied around the difficulties of data processing and system performance analysis of AMPC SAR. In the second chapter, the intrinsic principle and signal model of AMPC SAR are described. By analyzing the quality factor and the minimum antenna area, it is revealed that the essence of AMPC SAR system is to reconfigure the traditional single antenna array and realize the HRWS observation by combining the azimuth digital beamforming (DBF) technology. The cost is the sensitivity of the system. By analyzing the characteristics of spatial sampling, the generalized uniform sampling PRF expression is given, and the equivalent PRF expression based on DPCA reconstruction is given. In the third chapter, the problems of AMPC SAR signal reconstruction and performance analysis are studied. The conventional signal reconstruction method can only reconstruct the clutter spectrum whose width is integer times of PRF, which leads to the extreme deterioration of the reconstructed performance under special PRF conditions. Therefore, strict requirements are put forward for the system parameter design. A modified echo spectrum model is established to extend the reconstructed signal bandwidth to arbitrary values rather than local. Limited to integer multiple PRF, the robustness of conventional signal reconstruction methods is improved and the degree of freedom of system parameter design is improved significantly. A unified DBF processing framework for AMPC SAR signal reconstruction is established based on modified echo spectrum model. Under this framework, the reconstruction performance of a series of signal reconstruction methods is analyzed and compared, so as to achieve signal weight. In Chapter 4, the modeling and correction of array errors are studied. The channel response error and the phase center position error are modeled as the yaw position error, amplitude error and phase error of the array. It is pointed out that the phase center position error will lead to larger phase error. Based on the attenuation characteristics of clutter power spectrum, a new array error estimation method is proposed, which takes the ratio of the power at both sides of the clutter spectrum to the power at the center of the clutter spectrum as the optimization objective and obtains robust error estimation performance. The modified orthogonal subspace method can obtain robust error estimation performance based on the orthogonality of signal subspace and noise subspace under the condition of fewer channels. A phase error fitting method based on array error model is proposed to estimate the spatially varying phase errors in AMPC SAR data quickly and accurately. Chapter 5 is devoted to the study of dual-directional SAR (BiDi-SAR) imaging technology based on AMPC. Single-channel BiDi-SAR has strict requirements for PRF. In this paper, AMPC BiDi-SAR observation mode is proposed, and a spectrum separation method based on LS algorithm is proposed, which can significantly reduce the severe requirements of PRF and significantly improve the observation of BiDi-SAR system. The simulation and experimental data processing results verify the correctness of the relevant theoretical analysis and the validity of the signal processing method proposed in this paper, thus providing a strong support for HRWS-oriented AMPC SAR system parameter design and real-time data processing.
【学位授予单位】：国防科学技术大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN958
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