Performance of a radar system is affected by unpleasant variations, due to changes in operating conditions of the radar environment. The well-known approach that may be used to deal with these performance variations is using adaptive detectors, which can adapt themselves with these conditions and variations, instead radars with constant processing structure. According to these properties, detection and estimation theory are used in designing the adaptive detectors and up to now, several adaptive detectors have been designed. In many adaptive detection techniques, a set of training data (called secondary sample data) from the range cells close to the range cell under test (CUT) is used to improve the ability of adapting to the environment and therefore improve the performance of the detector. It is assumed that only the CUT include target signal and secondary data involve merely interference. Moreover, they are assumed to be independent and identically distributed (iid) and also be representative of the interference statistics of the CUT. Such training data are called homogeneous. But under some circumstances such as clutter edge, clutter discrete and other interfering targets, these assumptions are not further true and the training data becomes nonhomogeneous. As a result, the performance of adaptive detectors is degraded. In this thesis, after studying the performance of adaptive detectors in nonhomogeneous environment and recalling methods to remove nonhomogeneous samples from training data, a novel effective and numerically efficient method is proposed and used to improve the performance of the adaptive detectors by detecting the nonhomogeneous data and removing them. Also using suitable models for interference and target and using detection theory methods, some new adaptive detectors are designed so that they consider interfering targets at their structures and is shown that they have better performance in nonhomogeneous environment compared with preceding designed detectors by computer simulations. Key Words: Detection Theory, Adaptive detector, Interfering targets
