Performance analysis of the excision CFAR detection techniques with contaminated reference channels

Abstract

Abstract The presence of one or more interfering target returns amongst the reference cells causes the adaptive threshold to increase erroneously. This effect makes a major source of performance impairment for some types of cell-averaging detectors. To improve the radar performance in this situation, it is natural to attempt to remove these interferers from the reference samples before establishing the detection threshold. The excision cell-averaging (EXCA) technique carries out this task by excising strong samples, that exceed an excision threshold, from the reference window prior to making the cell-averaging operation. The ML detection is used in radar systems to control the increased false alarm probability that occurs in nonstationary noise environment. On the other hand, the MAX operation is included to control false alarms at clutter edges and the MIN operation is proposed to resolve closely spaced targets. For these reasons, we introduced the ML-EXCA, MX-EXCA and MN-EXCA for radar target detection. This paper provides a complete detection analysis for these schemes in both a homogeneous environment and in an environment of an arbitrary number of outlying targets. A Swerling II target fluctuation is used as a model for the received signal and only single pulse detection in considered.