基于Grubbs法则的改进CAG-CFAR检测器

A Refined CAG-CFAR Detector Based on Grubbs Criterion

针对传统恒虚警检测器在多目标情况下出现性能下降的问题,提出了一种基于格拉布斯(Grubbs)法则的改进CAG-CFAR检测器,即CAGp-CFAR检测器。该方法利用Grubbs法则实现对参考窗中奇异值、干扰目标的有效剔除,极大地降低了多目标环境中均值类恒虚警检测器的“遮盖效应”,在多目标环境下具备良好的应用潜力。考虑到CAG-CFAR检测器进行野值剔除时对样本概率密度函数存在一定限制,本文算法进一步对CAG-CFAR检测器的复杂结构进行了合理简化,具备更强的工程应用价值。仿真结果表明该方法在各类典型杂波背景中都具备良好的检测性能。

In this paper,a refined CAGp-CFAR detector based on Grubbs criterion is proposed.The proposed method is feasible in multipletarget scenario,in which the traditional CFAR detectors will suffer performance degradation in varying extent.The outliers and interfering targets embedded in the reference window can be rejected effectively through Grubbs criterion.Consequently,the "masking effect"in the class of cell averaging CFAR detectors is eliminated significantly,which will be beneficial to target detection in multiple-target scenarios.By simplifying the structure of CAG-CFAR detector,the CAGp-CFAR detector performs effectively in practical situations.Simulation results demonstrate the superiority of the proposed method in different clutter backgrounds.