基于lk范数的SAR复图像域正则化方法分析及改进

正则化方法通过增加先验信息约束实现合成孔径雷达(SAR)图像的超分辨和噪声抑制，为目标识别提供了更高质量的图像信息。该文通过对基于lk范数的SAR复图像域正则化方法迭代过程的分析，揭示其增强分辨率的内在机理，并针对原有方法在不同强度散射点条件下分辨率提高不一致的问题，提出采用可变的正则化参数对其进行改进。仿真数据和MSTAR实测数据的实验结果证实了改进方法的有效性。

Analysis and Improvement of Regularization Based on l_k Norm in SAR Complex-Imagery Domain

Regularization technique can accomplish super-resolution and noise suppression by imposing prior information, which provides high quality image for target recognition. The iterative process of SAR complex imagery domain regularization based on l_k norm is analyzed to reveal the inherent principles of super-resolution. Because of the inconsistent resolution problem of the original algorithm for different amplitude scattering centers, an improved method based on varying parameters is proposed. Simulation experiments and computational results of measured MSTAR data prove the effectiveness of the proposed method.