Design and Implementation of a CFAR Processor for Target Detection

Real-time performance of adaptive digital signal processing algorithms is required in many applications but it often means a high computational load for many conventional processors. In this paper, we present a configurable hardware architecture for adaptive processing of noisy signals for target detection based on Constant False Alarm Rate (CFAR) algorithms. The architecture has been designed to deal with parallel/pipeline processing and to be configured for three versions of CFAR algorithms, the Cell-Average, the Max and the Min CFAR. The architecture has been implemented on a Field Programmable Gate Array (FPGA) with a good performance improvement over software implementations. Results are presented and discussed.