Moving Target Detection Using CA, SO and GO-CFAR detectors in Nonhomogeneous Environment

Abstract

Modernization of radar technology and improved signal processing techniques are necessary to improve detection systems in complex situations. A fundamental problem in radar systems is to automatically detect targets while maintaining a desired constant false alarm probability. This work studies two detection approaches, the first with a fixed threshold and the other with an adaptive one. In the latter, we have learned the three types of detectors CA, SO, and GO-CFAR. This research aims to apply intelligent techniques to improve detection performance in a nonhomogeneous environment using standard CFAR detectors. The objective is to maintain the false alarm probability and enhance target detection by combining intelligent techniques. With these objectives in mind, implementing standard CFAR detectors is applied to nonhomogeneous environment data. The primary focus is understanding the reason for the false detection when applying standard CFAR detectors in a nonhomogeneous environment and how to avoid it using intelligent approaches