Constant false alarm rate detection in Gauss distributed environments

Classical radar receivers are designed to work with a constant threshold to keep false alarm fixed on the assumption that the statistics of the environment is known a priori. However, in environments, in which noise or clutter level are not known or are changing, radars which have receiver, with fixed threshold level, show performance degradation. Constant False alarm Rate (CFAR) algorithms are used to detect the targets by guessing noise and clutter power level of environments whose statistics are not known or are changing. In this thesis, probability of false alarm and probability of detection of Cell Averaging Constant False Alarm Rate (CA-CFAR), Greatest of Constant False Alarm Rate (GO-CFAR), Smallest of Constant False Alarm Rate (SO-CFAR) methods are examined and compared in the homogeneous and non-homogeneous mutiple target and clutter edge power transition environments.