论文部分内容阅读
提出一种新的基于有序统计的恒虚警检测器和一种新的自动筛选技术。这种新的检测器是广义有序统计单元平均（ＧＯＳＣＡ）恒虚警算法。对这种新的恒虚警算法在斯威林２型目标假设下，我们获得了虚警概率、探测概率和度量ＡＤＴ的解析表达式。在均匀背景和强干扰存在的情况下，分析了它的探测性能，并把它与ＯＳ－ＣＦＡＲ进行了比较。分析结果表明，ＧＯＳＣＡ－ＣＦＡＲ在均匀干扰背景和多目标情况下均具有较好的探测性能，而ＧＯＳＣＡ－ＣＦＡＲ参考滑窗单元幅值排序的处理时间还不到ＯＳ－ＣＦＡＲ的一半。
A new CFAR detector based on ordered statistics and a new automatic screening technique are proposed. The new detector is a generalized ordered statistical unit-average (GOSCA) constant false alarm algorithm. For this new CFAR algorithm, we obtain the analytic expressions of false alarm probabilities, probabilities of probabilities and ADTs under the assumption of the Swain-2 target. In the presence of uniform background and strong interference, its detection performance was analyzed and compared with OS-CFAR. The analysis results show that GOSCA-CFAR has better detection performance under uniform interference background and multiple targets, while the GOSCA-CFAR reference sliding window unit magnitude processing time is less than half of OS-CFAR.