Performance of the VI-CFAR in Homogeneous Weibull Background

We study the performance of the newly proposed VI-CFAR in Weibull clutter. The VI-CFAR is a composite CFAR processor that dynamically selects between different conventional adaptive thresholding algorithms, depending on the background environment, in order to maintain constant false alarm rate (CFAR). It utilizes the concept of data variability, and computes a second-order statistic called the variability index (VI) to dynamically tailor the background estimation algorithm. Previously this type of CFAR has only been studied for the case of Gaussian background clutter. However, studies show that the Weibull distribution provides a better fit for many clutter situations. The VI-CFAR parameters for the case of Weibull clutter have been designed and performance curves for the homogeneous background case have been plotted. Results show that the VI-CFAR processor has satisfactory performance with low CFAR loss