典型线面目标合成孔径雷达参数化成像

在复杂场景(特别是城区场景)合成孔径雷达(SAR)遥感成像中，存在大量线、面目标，如城区中的道路和建筑物边缘等目标，这些线面目标微波散射信号方向性强。传统SAR从单一视角获取场景的散射信息，且传统成像算法均基于点目标模型，使得传统SAR图像中线面目标主要特征表现为一系列的强散射点，而非线散射特征和面散射特征，最终造成SAR图像中目标不连续，SAR图像解译困难。因此，该文通过建立典型线段、三角面元目标的参数化回波模型，对线面目标SAR成像机理进行了深入细致的研究；并基于提出的参数化模型对线面目标进行参数化成像，即首先基于贝叶斯理论和所提的参数化模型对典型的线面目标进行分类判决，随后采用再成像的方式获得有效表征线、面目标散射特征的SAR图像，为线、面目标SAR图像解译提供有效支撑。最后，数值仿真实验成功验证了所提算法的有效性和正确性。 

Parametric SAR Imaging for Typical Lines and Surfaces

In the Synthetic Aperture Radar(SAR)remote sensing imagery of complicated scenes(especially urban scenes),there are a large number of lines and surfaces,such as roads in urban areas and the surfaces of buildings.These microwave-signal-scattering features have strong directivity.Traditional SAR acquires the scattering information of a scene from a single observation,and traditional imaging algorithms are based on the point target model,which makes the main features of the lines and surfaces in traditional SAR images appear as a series of strong scattering points rather than line-scattering and surface-scattering features.This outcome ultimately causes the target to be discontinuous in the SAR image,thus making the SAR image difficult to interpret.Therefore,in this study,we conducted an in-depth and meticulous investigation of the SAR imaging mechanism for lines and surfaces by establishing a parametric echo model of typical lines and triangular surfaces.Based on the proposed parametric model,we performed parametric imaging of these lines and surfaces.Based on our results,we propose a parametric imaging method,in which the typical lines and surfaces are classified and determined based on Bayesian theory and the proposed parametric model.Then,an SAR image can be obtained that effectively characterizes the scattering features of the line and surface targets by visual imaging,which effectively facilitates SAR image interpretation.The results of our numerical simulation experiments verify the validity of the proposed method.