一種新的基于剔除平均的最大選擇恒虛警檢測器
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)提出了一種新的最大選擇(GO)恒虛警檢測器,它的前、后沿滑窗均采用TM來產(chǎn)生局部估計,再選擇兩者之中的最大值作為檢測器對雜波功率水平的估計,去設置自適應檢測門限,并應用了何友(1994)提出的自動篩選技術。分析結果表明,它在均勻背景及多目標和雜波邊緣引起的非均勻背景中的性能,均比GOSGO或OSGO獲得了改善,并且它的樣本排序時間還不到OS的一半。一些流行的恒虛警方法如GO、GOSGO或OSGO、CMGO可看作是TMGO的特例。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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