改进的L1/2阈值迭代高分辨率SAR成像算法

Improved L1/2 Threshold Iterative High Resolution SAR Imaging Algorithm

针对合成孔径雷达(SAR)在稀疏采样条件下方位向分辨率低、易受噪声干扰等问题,提出改进的高分辨率SAR成像算法。该文在现有的L1/2正则化理论及其阈值迭代算法的基础上,改进了其表达式中的梯度算子,提高重构图像的求解精度,降低计算量。然后,在全采样和欠采样条件下,将原有L1/2阈值迭代算法与所提改进L1/2阈值迭代算法,分别结合近似观测模型对SAR回波信号进行成像处理和性能对比。实验结果表明,改进的算法具有更加优越的收敛性能,并且对于SAR图像方位向分辨率有一定的改善。

An improved Synthetic Aperture Radar(SAR)imaging algorithm is proposed to address the issues of low azimuth resolution and noise interference in the sparse sampling condition.Based on the existing L1/2 regularization theory and iterative threshold algorithm,the gradient operator is modified,which can improve the solution accuracy of the reconstructed image and reduce the load of calculation.Then,under full sampling and under-sampling conditions,the original and improved L1/2 iterative threshold algorithm are combined with the approximate observation model to image SAR echo signals and compare their imaging performance.The experimental findings demonstrate that the improved algorithm improves the azimuth resolution of SAR images and has higher convergence performance.