一种新的基于剔除平均的最大选择恒虚警检测器
A NEW GREATEST OF SELECTION CFAR DETECTOR BASED ON TRIMMED MEAN
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摘要: 本文基于剔除平均(TM)提出了一种新的最大选择(GO)恒虚警检测器,它的前、后沿滑窗均采用TM来产生局部估计,再选择两者之中的最大值作为检测器对杂波功率水平的估计,去设置自适应检测门限,并应用了何友(1994)提出的自动筛选技术。分析结果表明,它在均匀背景及多目标和杂波边缘引起的非均匀背景中的性能,均比GOSGO或OSGO获得了改善,并且它的样本排序时间还不到OS的一半。一些流行的恒虚警方法如GO、GOSGO或OSGO、CMGO可看作是TMGO的特例。
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关键词:
- 雷达; 检测; 恒虚警率; 有序统计
Abstract: A new greatest of selection CFAR detector (TMGO) based on trimmed mean (TM) is proposed in this paper. It takes the greatest value of two local estimations created by leading and lagging reference window which apply TM method as a noise power estimation, and it also uses the automatic censoring technique proposed by He You (1994). It is shown that the detection performance of TMGO is superior to that of GOSGO or OSGO in both homogeneous background and nonhomogeneous environment caused by strong interfering targets and clutter edges, while the sample sorting time of TMGO is less than a half of that of OS. Some current CFAR algorithms such as GO,GOSGO or OSGO, CMGO becomes the special cases of TMGO. -
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