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Analysis of some modified ordered statistic CFAR: OSGO and OSSO CFAR

机译:分析一些修改后的有序统计CFAR:OSGO和OSSO CFAR

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摘要

It is necessary for automatic detection radars to be adaptive to variations in background clutter in order to maintain a constant false alarm rate (CFAR). A CFAR based on an ordered statistic technique (OS CFAR) has some advantages over the cell-averaging technique (CA CFAR), especially in clutter edges or multiple target environments; unfortunately the large processing time required by this technique limits its use. The authors present two new OS CFARs that require only ahlf the processing time. One is an ordered statistic greatest of CFAR (OSGO), while the other is an ordered statistic smallest of CFAR (OSSO). The OSGO CFAR has the advantages of the OS CFAR with only a negligible increment to the CFAR loss.
机译:为了保持恒定的误报率(CFAR),自动检测雷达必须适应背景杂波的变化。与单元平均技术(CA CFAR)相比,基于有序统计技术(OS CFAR)的CFAR具有一些优势,尤其是在杂乱边缘或多个目标环境中;不幸的是,该技术所需的大量处理时间限制了其使用。作者介绍了两个新的OS CFAR,它们仅需要一半的处理时间。一个是CFAR(OSGO)的最大有序统计,而另一个是CFAR(OSSO)的最小有序统计。 OSGO CFAR具有OS CFAR的优点,而CFAR损耗的增加可以忽略不计。

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