中文摘要：

提出了一种基于压缩感知（compressed sensing,CS）和恒虚警率（constant false alarm rate,CFAR）目标检测算法,用于合成孔径雷达（synthetic aperture radar,SAR）图像的目标检测。针对传统的均值类和有序统计量类CFAR目标检测算法,首先对每个局部滑窗的背景杂波像素利用压缩感知进行重建,以此来降低SAR图像相干斑现象的影响,然后利用重建后的数据进行杂波分布参数的估计,并利用CFAR检测器进行目标检测。在真实的SAR图像中证明了上述目标检测算法的有效性。

英文摘要：

In this paper,we propose a compressive sensing based CFAR target detection algorithm for remote sensing SAR image.Considered of the traditional mean value and statistic CFAR detection algorithm,firstly,the background clutter pixels of every local sliding window is rebuild by using CS,so that the speckle of the SAR image is decreased.Then,the distribution parameters of the clutter are estimate from the rebuild image.At last,a CFAR detector is used to obtain the detection result.The experiments on real images show that the proposed algorithm is effective.