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在已有的恒虚警处理算法中，由于单元平均（ＣＡ）和有序统计（ＯＳ）法都是剔除平均（ＴＭ）法的特例，因此可以考虑用ＴＭ法代替一些参量ＣＦＡＲ算法中所采用的ＣＡ或ＯＳ法，以期获得更优的检测或控制虚警的性能。基于这种思想提出ＴＭＣＡＧＯ检测器，并在ＳｗｅｒｌｉｎｇⅡ型目标假设下推导Ｐｆａ、Ｐｄ和ＡＤＴ的解析表示式。通过对其在均匀背景和强干扰目标环境下性能的分析，以及与ＯＳＣＡＧＯ、ＧＯＳＧＯ和ＯＳ等检测器性能的比较，发现ＴＭＣＡＧＯ在上述环境中的性能较这几种检测器均获得了明显的改善。
In the existing CFAR algorithm, since both the cell average (CA) and the ordered statistics (OS) are special cases of the exclusion averaging (TM) method, it can be considered to replace some of the parametric CFAR algorithms with TM The CA or OS method, in order to obtain better detection or control of false alarm performance. Based on this idea, the TMCAGO detector was proposed and the analytic expressions of Pfa, Pd and ADT were deduced under the Swerling Ⅱ target hypothesis. Through the analysis of its performance under uniform background and strong interference target environment and the comparison with the detector performance of OSCAGO, GOSGO and OS, it is found that the performance of TMCAGO in these environments has been significantly improved compared with these detectors .