In this paper, the zlog(z) based estimator for constant false alarm rate (CFAR) detection in Weibull clutter is proposed. This estimation method is obtained in terms of the digamma function where the estimates of the shape parameter are determined by the interpolation tool. The non-integer order moments estimator (NIOME) is also given and coincides the zlog(z) estimation results for low values of the moment’s fractional order. Via simulated data, it is shown that the CFAR detection performances based on the zlog(z) estimator have almost similar results as well as the existing maximum likelihood (ML) CFAR detector, but with low time-consuming which is very important in real-time applications.

本文提出了一种基于zlog（z）的估计器，用于威布尔杂波中的恒定虚警率（CFAR）检测。该估计方法是根据digamma函数获得的，其中形状参数的估计由插值工具确定。还给出了非整数阶矩矩估计器（NIOME），它与矩分数阶的低值的zlog（z）估计结果一致。通过模拟数据表明，基于zlog（z）估计器的CFAR检测性能与现有的最大似然（ML）CFAR检测器几乎具有相似的结果，但耗时很短，这在实际操作中非常重要时间应用程序。