单元筛选后作最大选择的CFAR自适应检测器

提出一种新的CFAR自适应检测方法，对这种新的检测方法在斯威林2型目标的假设下进行了检测性能的分析，得到了在均匀背景和强干扰目标存在的情况下的虚警概率和检测概率，并把它同CA、GO、SO等检测方法进行了比较。分析结果表明：这种方法在均匀背景和非均匀背景情况下都有很好的检测性能。

A GO-CFAR Adaptive Detector Based on Cell Selection

A new CFAR adaptive detection method is developed and its detection performance is analyzed under the Swerling 2 assumption.We obtain its false alarm rate and detection probabilities in homogeneous background and in the presence of strong interfering targets, and compare it to the other methods such as CA CFAR, GO CFAR, SO CFAR, etc.The results indicate that this method has better detection performance in both homogeneous environments and nonhomogeneous environments.