Binary and fuzzy distributed CFAR detectors

In this paper, two types of distributed constant false alarm rate (CFAR) detectors; binary and fuzzy distributed detectors, are introduced. In these two types of distributed detectors, it was assumed that the clutter parameters at the local sensors are unknown and each local detector performs CFAR processing based on maximum likelihood (ML) and order statistic (OS) CFAR processor before transmitting data to the fusion center. At the fusion center, received data are weighted by a binary or a fuzzy weighting function, and combined according to deterministic rules, constructing global test statistics. In the binary and fuzzy types, we consider the various distributed detectors based on binary and fuzzy rules used in fusion center and CFAR detector used in local detectors. The performance of the two types of distributed detectors are analysed and compared with each other. The simulation results indicate the superiority and robust performance of fuzzy type in homogenous and non-homogenous situations.