CFAR DATA FUSION CENTER WITH INHOMOGENEOUS RECEIVERS

Detection system with distributed sensors and data fusion, are increasingly being used by surveillance systems. In this work a system formed by N inhomogeneous constant false alarm rate (CFAR) detectors (cell-averaging (CA) and ordered statistic (OS) CFAR detectors) is studied. A recursive formulation is presented or an algorithm that permits for a fixed level of false alarm in the data fusion center, to set the optimum individual threshold levels in the CFAR receivers and the optimum "K out of N" decision rule in order to maximize the total probability of detection. The algorithm also considers receivers of different quality or with different communication channel qualities connecting them with the fusion center. This procedure has been applied to several hypothetical networks with distributed CA-CFAR and OS-CFAR receivers and for Rayleigh targets and interference, enabling the inference that in general the fusion decision OR rule is not always the best.