面向目标特性精细提取的SAR数据融合成像处理方法

针对当前高分辨率星载SAR数据处理忽略目标相关散射特性随方位角变化而导致目标轮廓细节难以精细提取的问题，该文提出了一种面向目标特性精细提取的融合成像处理方法。首先，分析高分辨率条件下影响目标特性提取和SAR图像质量的因素，如轨道非线性、停-走模型、大气延时、高阶残留相位误差等，并提出针对性的补偿方法。在此基础上，建立基于目标时空谱特性的回波数学信号模型，解析目标散射特性时-空-频的变化规律，提出针对高分辨率、超大方位观测角范围的融合成像处理策略和方法，在距离-多普勒域、图像域通过融合处理提升SAR图像的品质。最后，通过对典型军事目标的仿真和成像处理，验证所提方法的有效性。 

SAR Data Fusion Imaging Method Oriented to Target Feature Extraction

To deal with the difficulty for target outlines extracting precisely due to neglect of target scattering characteristic variation during the processing of high-resolution space-borne SAR data, a novel fusion imaging method is proposed oriented to target feature extraction. Firstly, several important aspects that affect target feature extraction and SAR image quality are analyzed, including curved orbit, stop-and-go approximation, atmospheric delay, and high-order residual phase error. Furthermore, the corresponding compensation methods are addressed as well. Based on the analysis, the mathematical model of SAR echo combined with target space-time spectrum is established for explaining the space-time-frequency change rule of target scattering characteristic. Moreover, a fusion imaging strategy and method under high-resolution and ultra-large observation angle range conditions are put forward to improve SAR quality by fusion processing in range-doppler and image domain. Finally, simulations based on typical military targets are used to verify the effectiveness of the fusion imaging method.