Performance comparison of some censoring CA-based CFAR processors in heterogeneous environments

Abstract

Performance comparison of automatic censoring CA-based CFAR processors contribute to the development of more efficient censoring detectors. In this paper, the authors analyze the performance of the detection schemes which named: ACCA-odv- (Automatic Censored Cell Averaging -ordered data variability-), ADCCA- (Automatic Dual Censoring Cell Averaging-), ACGCA- (Automatic Censoring Greatest Cell Averaging-), and GGDC- (Goodness-of-fit Generalized likelihood test with Dual Censoring-)-CFAR's in heterogeneous environments. The assumed environments are represented by three situations: first, the homogeneous situation, second, the presence of interfering targets, and the third case is allowed to the presence of clutter edges. The obtained results, under the assumption of a Gaussian clutter and a mono pulse processing, show that most of the studied detectors perform well in a specific conditions and there is a need to further developments to ensure the required performances for recent target detection application.