An IOSGO-CFARAlgorithm based on Clutter Classification and Recognition

Abstract

Constant False Alarm Rate(CFAR)processing is one of the most critical technologies in radar signal processing, and its purpose is to guarantee a constant false alarm rate during the detection for targets. However, the general CFAR processing is predicated on the clutter distribution characteristics, and different clutter distributions correspond to different CFAR processing algorithms. In order to improve detection performance in different clutter distributions, in this paper we proposes an IOSGO-CFAR algorithm, This method uses the number of interference targets that S-CFAR can tolerate to determine whether it is a homogeneous environment or a non-homogeneous environment. When the number of tolerable interference targets is set to zero, this is a homogeneous enviroment and the CA-CFAR algorithm is selected. Once the interference target is detected, this is a nonhomogeneous environment and the OSGO-CFAR algorithm is selected. When CFAR is 10−4, the algorithm simulation of IOSGO-CFAR shows that IOSGO-CFAR has better detection performance. Finally, the verification of FPGA is carried out and the clock frequency can reach 154.967 MHz.