论文部分内容阅读
基于有序统计和单元平均方法及文献［１］中的自动筛选技术，提出了一种新的恒虚警检测器。它被称作排序与平均均值（ＭＯＳＣＡ）处理器。对这种新的恒虚警检测器，在ＳｗｅｒｌｉｎｇⅡ型目标假设下，我们获得了虚警和检测概率度量ＡＤＴ的解析表达式。在均匀背景和存在强干扰目标的情况下，分析了它的检测性能，并将其与ＣＡ和ＯＳ－ＣＦＡＲ进行了比较。结果表明，ＭＯＳＣＡ－ＣＦＡＲ在均匀干扰背景中的性能位于ＣＡ和ＯＳ之间，在多目标情况下明显好于ＯＳ－ＣＦＡＲ检测器。
Based on the orderly statistics and the unit average method and the automatic screening technology in [1], a new CFAR detector is proposed. It is called the Sort and Mean (MOSCA) processor. For this new constant false alarm detector, under the SwerlingⅡtype objective assumption, we obtain the analytic expression of the false alarm and detection probability measure ADT. In the case of uniform background and the existence of strong interference targets, its detection performance was analyzed and compared with CA and OS-CFAR. The results show that the performance of MOSCA-CFAR in the context of uniform interference lies between CA and OS and is significantly better than that of OS-CFAR detector in multi-target case.