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A Configurable FPGA-based Hardware Architecture for Adaptive Processing of Noisy Signals for Target Detection Based on Constant False Alarm Rate (CFAR) Algorithms

In this paper, we present a configurable FPGA-based 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 processing and to be configured for three versions of CFAR algorithms, the Cell-Average, the Max and the Min CFAR. The proposed pipelined architecture has been implemented on a Field Programmable Gate Array (FPGA) device providing good performance improvements over software implementations. FPGA implementation results are presented and discussed.