自动删除恒虚警率算法(AC-CFAR)作为一种自适应的CFAR检测算法被广泛应用于目标检测中,文中引入均值比 对自动删除恒虚警率算法进行改进,使得其在杂波边缘处也有很好的检测效果。在检测过程中,通过分析4个不同方向 的均值比来判断边缘方向,能够很好地解决边缘对检测结果的影响。采用能对高分辨率SAR图像精确建模的G0分布进 行杂波区域建模,通过更加准确地对背景区域数据的拟合,进一步提高了检测精度。实验表明改进后的算法不仅在同质 区域和多目标区域有很好的检测效果,在杂波边缘处也能取得比较好的检测效果。

Automatic censoring CFAR (Constant False Alarm Rate) is widely used in target detection as an adaptive CFAR algorithm. A modified algorithm is proposed in this paper. The algorithm improves the performance of target detection in clutter edges by introducing the mean ratio to detection procedure. Moreover, the algorithm improves the detection accuracy by using the G0 distribution to model high resolution SAR image accurately in the broad uniform change area. The experimental results show that the modified algorithm performs well in both the homogeneous area and clutter edges.

中国博士后科学基金资助项目