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A new CFAR detector based on ordered statistics and cell averaging

机译:一种基于有序统计和单元平均的新型CFAR检测器

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This paper presents a new CFAR detector based on ordered statistics and cell averaging, as well as the automatic censoring technique. It is known as "mean of order statistics and cell averaging" (MOSCA) processor. For this new CFAR detector we obtain analytic expressions of the false alarm rate, the detection probabilities and measure average decision threshold (ADT) under the Swerling II assumption. Its detection performance is analyzed in homogeneous background and in the presence of strong interfering targets, and we compare it with CA and OS CFARs. The analysis shows that performance of the MOSCA-CFAR detector is between the CA and OS CFAR processor in homogeneous background. In multiple target situations the MOSCA-CFAR detector is much better than the OS-CFAR detector.
机译:本文提出了一种新的基于有序统计和像元平均的CFAR检测器,以及自动检查技术。它被称为“顺序统计和单元平均法”(MOSCA)处理器。对于这种新的CFAR检测器,我们在Swerling II假设下获得了误报率,检测概率和度量平均决策阈值(ADT)的解析表达式。在均质背景下和存在强干扰目标的情况下分析了其检测性能,并将其与CA和OS CFAR进行了比较。分析表明,在同类背景下,MOSCA-CFAR检测器的性能介于CA和OS CFAR处理器之间。在多个目标情况下,MOSCA-CFAR检测器比OS-CFAR检测器好得多。

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