一种基于压缩感知恢复算法的SAR图像方位模糊抑制方法

Azimuth Ambiguity Suppression in SAR Images Based on Compressive Sensing Recovery Algorithm

方位模糊现象广泛存在于星载合成孔径雷达图像中。当模糊能量较强时,会出现大量的虚假目标,严重影响对图像的判读。由于模糊能量与真实主区能量在时域、频域中均互相混叠,现有的处理方法很难在不损失分辨率的条件下,有效抑制方位模糊所产生的"鬼影"。该文提出一种基于压缩感知恢复算法的方位模糊抑制方法,通过截断图像的多普勒频谱实现模糊抑制,而后将原始图像作为先验信息、将截断谱作为观测结果,利用压缩感知恢复算法,迭代求解出高分辨率的图像。经过仿真与真实数据验证,该方法可以有效抑制方位模糊能量,而不损失主区目标分辨能力,且对复杂场景同样具有良好的效果。

Azimuth ambiguities appear widely throughout spaceborne Synthetic Aperture Radar（SAR） images.If the ambiguous energy is relatively strong,a large number of brilliant areas or points will emerge,which may be erroneously judged as actual targets.This is a disadvantage in image interpretation.Due to the fact that ambiguous energy is mixed with energy from the main zone in the frequency and time domains,it is difficult to suppress azimuth ambiguity to a reasonable level using the existing approach without loss of resolution.This study proposes an innovative approach for suppressing azimuth ambiguity based on the compressive sensing recovery framework,in which the original image acts as prior information and the corresponding frequency spectrum truncated in a proper ratio acts as measurement information.With the proposed approach,highresolution low-ambiguity images can be obtained by iteration.We used simulation and satellite data to validate the effectiveness of this proposed approach in suppressing azimuth ambiguity.