An Overview of Design and Implementation of Various Ordered Statistical Methods for Target Detection in RADAR

In case of target detection, the background environment is not always homogeneous. Rather, most of the times, it is filled with non-homogeneities like multiple targets and reverberation edges. Cell Averaging Constant False Alarm Rate (CA-CFAR) gives better performance in a homogeneous environment, but its performance decreases in the presence of non-homogeneities and in the presence of multiple targets. No other CFARs give the best performance in both homogeneous and Non- homogeneous environments at the same time. Variability Index CFAR (VI-CFAR) is a combined CFAR approach that adapts itself to CA-CFAR, GO-CFAR, or SO-CFAR depending on whether the background environment is homogeneous, has reverberation edges, or has multiple targets, respectively. This adaptability is based on the values of the Mean Ratio (MR) and the Variability index (VI) calculated from the leading or lagging CFAR reference windows. This paper discusses various CFAR processing techniques with their advantages and disadvantages.