Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA.
IEEE Trans Image Process. 2001;10(4):623-31. doi: 10.1109/83.913596.
We develop a method for the formation of spotlight-mode synthetic aperture radar (SAR) images with enhanced features. The approach is based on a regularized reconstruction of the scattering field which combines a tomographic model of the SAR observation process with prior information regarding the nature of the features of interest. Compared to conventional SAR techniques, the method we propose produces images with increased resolution, reduced sidelobes, reduced speckle and easier-to-segment regions. Our technique effectively deals with the complex-valued, random-phase nature of the underlying SAR reflectivities. An efficient and robust numerical solution is achieved through extensions of half-quadratic regularization methods to the complex-valued SAR problem. We demonstrate the performance of the method on synthetic and real SAR scenes.
我们开发了一种用于形成具有增强特征的聚束式合成孔径雷达（SAR）图像的方法。该方法基于散射场的正则化重建，它将 SAR 观测过程的层析成像模型与关于感兴趣特征的性质的先验信息相结合。与传统的 SAR 技术相比，我们提出的方法生成的图像具有更高的分辨率、更低的旁瓣、更少的斑点和更容易分割的区域。我们的技术有效地处理了基础 SAR 反射率的复值、随机相位性质。通过将半二次正则化方法扩展到复值 SAR 问题，实现了高效和稳健的数值解。我们在合成和真实 SAR 场景上展示了该方法的性能。
