一种采用自动筛选技术的鲁棒恒虚警检测器

A ROBUST CFAR DETECTOR WITH AUTOMATIC CENSORING TECHNIQUE

本文基于有序统计（ＯＳ）和筛选平均（ＣＭ）提出了一种新的恒虚警检测器，它采用ＯＳ和ＣＭ方法来产生局部估计，再采用二者的平均值作为对杂波功率水平的估计，并应用了文献［５］提出的自动筛选技术，在ＳｗｅｒｌｉｎｇⅡ型目标假设下，本文推导出了它的Ｐｆａ、Ｐｄ和度量ＡＤＴ的解析表达式，并与其它方案进行了比较。分析结果表明，它对均匀背景和多目标环境均具有适应性，尤其是在多目标引起的非均匀背景场合中，它呈现较好的锝棒性，它的性能与ＯＳ相比有较大的改善，并且它的样本排序时间不及ＯＳ、ＣＭ的一半。

In this paper a new CFAR detector(MOSCM)based on order statistics(OS)and censored mean(CM)is proposed It selects the mean value of OS and CM local estimations as a globle noise power estimation for the detector,and it also uses the automatic censoring technique proposed You He Under SwerlingⅡ assumption,the analytic expression of P fa ,P d and ADT of MOSCM are derived By comparison with other schemes,the results show that MOSCM CFAR detector has an adaptability for both homogeneous background and nonhomogeneous background caused by multiple interfering targets,particularly in multiple target situations,it exhibits good robustness,the detection performance is improved,and its sample sorting time is less than half of that of OS,CM