Faycal Khaldi and Faouzi Soltani, Universite des Freres Mentouri Constantine, Algeria

In this paper, we propose to use fuzzy fusion rules to improve the performances of the Cell Averaging Constant False Alarm Rate (CA-CFAR) detector for MIMO (Multiple Input Multiple Output) radars in homogenous background modeled by a Pareto distribution. We compute the membership function for each individual detector. The global membership function at the fusion centre is a combination of the membership functions collected from individual detectors using four fusion rules, namely; the “MIN”, “MAX”, “algebraic product” and the “algebraic sum”. By means of Monte Carlo simulations, we evaluated the performance of the global system. The obtained results showed that for a number of nodes equal to four, the performance is the best for a high number of receivers and a low number of transmitters. For the best case and in homogenous background, the “algebraic product” fusion rule gives the best result when SNR >4 dB whereas the “algebraic sum” is the best when SNR <4 dB for the CA-CFAR.

Radar detection, MIMO, Fuzzy rules, Homogeneous clutter, CFAR