一种新的最小选择恒虚警检测器

A New Smallest of Selection CFAR Detector

本文基于有序统计(OS)和剔除平均(TM)提出了一种新的恒虚警检测器(OSTMSO),它采用OS和TM来生产局部估计,再采用最小选择逻辑来实现对杂波功率水平的估计,并应用了文献[4]提出的自动筛选技术.在SwerlingⅡ型目标假设下,推导出了它的P_(?)P_d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,OSTMSO在均匀背景及多目标环境中的性能都比GOSSO获得了改善,同时,它的样本排序时间还不到OS的一半.

A new CFAR delector (OSTMSO) based on order statistics (OS) and trimmed mean (TM) is proposed in this paper, It takes the smaltest value of OS and TM local estimations as a noise power estimation, and also uses the automatic censoring technique proposed by reference [4]. Under Swerling 11 assumption, the analytic expressions of P(? P(?) and ADT of OSTMSO are derived. By comparison with oilier schemes, the results show that the detection performance of OSTMSO in homogeneous background and in strong interfering targets cnvironment is superior to that of GOSSO. while the sample sorting time of OSTMSO is less than half of that of OS.