An Adaptive CFAR Processor based on Automatic Censoring Technique for Target Detection in Heterogeneous Environments

摘要

The performance of radar detection systems is affected by the presence of multiple interfering targets and/or clutter edges. In this paper, we propose an adaptive Constant False Alarm Rate (CFAR) detector for heterogeneous (non homogeneous) environments. The proposed Adaptive Cell Averaging Detector or ACAD-CFAR, uses an automatic cell by cell censoring technique to reject dynamically the unwanted echoes. In fact, the problem of target detection resides in the estimation of the transitions in the reference window. Also, the presence of unwanted irregularities in the considered reference canal increases the detection threshold. The suggested detector, which does not require any prior information about the observed background, provides a good detection of the unknown transitions and protects perfectly its adaptive threshold against the presence of undesired echoes. Depending on the obtained transitions, the proposed scheme follows a strategy to output its detection decision by using an IID (Independent and Identically Distributed) conversion. Monte-Carlo simulated results, under the assumption of Gaussian clutter and mono pulse treatment, show that the addressed CA- based processing performs like the conventional CA-CFAR (Cell Averaging-) detector in the homogeneous situation and exhibits good performance in non homogeneous environments caused by the presence of multiple secondary targets and/or clutter edges.