基于区域分类的智能恒虚警SAR图像目标检测

Intelligent CFAR Detector Based on Region Classification for SAR Images

提出了一种用于SAR图像目标检测的基于区域分类的智能恒虚警算法.该算法组合常规的单元平均恒虚警、选小恒虚警和选大恒虚警的有利特性,在多窗口划分和区域类型分类的基础上,实现目标的智能检测.实验表明,该方法在同质性区域保持较好检测性能的同时,在多目标和杂波边缘的异质性区域也有较强的鲁棒性.这必将极大的降低后续辨别和识别阶段的复杂度,从而提高了整个ATR系统的性能.

Based on multiple child-windows and region classification, this paper proposes a new intelligent CFAR method that makes a full use of CA-CFAR, SO-CFAR and GO-CFAR. The experimental results on SAR image show that the new method has a good detection performance not only in homogenous clutter background but also in non-homogenous clutter background including multi-target environment and clutter edge environment. This will greatly reduce the complexity of discrimination and classification in the next stage, and improve the performance of the whole ATR system.