In the presence of Weibull clutter, the development of sliding window detection processes, based on scale and power invariant distributions, has been extensively examined. This involves the selection of two functions labeled as scale-invariant and secondary CRP (clutter range profile) functions. However, due to the presence of outliers, existing CFAR (constant false alarm rate) algorithms show remarkable CFAR losses. We resort in this work to the practice of a suitable choice of these two functions in order to have a new decision rule with immunity against interfering targets. To do this, a quadruple-order statistics-based CFAR detection algorithm with different four-order statistics are proposed in the presence of log-normal and Weibull clutter disturbances. Via Monte Carlo simulations, the analysis of the false alarm regulation of the proposed detector is studied showing its robustness with respect to clutter parameters. Moreover, for comparison purposes with existing CFAR algorithms, simulated results indicate that lowest CFAR losses can be obtained by the proposed quadruple-order statistics named WHWH-CFAR (Weber–Haykin-Weber–Haykin) in the presence of strong interfering targets. IPIX real data are also performed to test the validity of the proposed detector.

在存在威布尔杂波的情况下，已经广泛研究了基于尺度和功率不变分布的滑动窗口检测过程的开发。这涉及选择标记为比例不变和次级CRP（杂波范围分布图）功能的两个功能。但是，由于存在异常值，现有的CFAR（恒定误报率）算法显示出明显的CFAR损失。我们诉诸这项工作的这两个功能的合适选择的做法，以有对干扰目标的免疫力一个新的决策规则。为此，提出了在对数正态和Weibull杂波干扰下，基于四阶统计量的CFAR检测算法，该算法具有不同的四阶统计量。通过蒙特卡洛模拟，研究了对所提出的探测器的虚警规则的分析，显示了其对于杂波参数的鲁棒性。此外，出于与现有CFAR算法的比较目的，模拟结果表明，在存在强干扰目标的情况下，可以通过提出的名为WHWH-CFAR（Weber-Haykin-Weber-Haykin）的四阶统计量来获得最低的CFAR损耗。还执行IPIX真实数据以测试所提出检测器的有效性。