一种基于有序统计和单元平均的CFAR检测器

He You, Guan Jian, Peng Ying-ning, Lu Dajin
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引用次数: 14

摘要

本文提出了一种新的基于有序统计和单元平均的CFAR检测器,并结合了自动滤波技术。它被称为“顺序统计和单元平均的平均值”(MOSCA)处理器。对于这种新的CFAR检测器,我们得到了在Swerling II假设下的虚警率、检测概率和测量平均决策阈值(ADT)的解析表达式。分析了其在均匀背景和强干扰目标下的检测性能,并与CA和OS CFARs进行了比较。分析表明,在均匀背景下,MOSCA-CFAR检测器的性能介于CA和OS CFAR处理器之间。在多目标情况下,MOSCA-CFAR检测器比OS-CFAR检测器要好得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new CFAR detector based on ordered statistics and cell averaging
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.
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