Performance analysis of a CA-CFAR detector in the interfering target and homogeneous background

摘要

An important part of radar processor is CFAR detector. In this paper, we propose a new cell-averaging constant false alarm rate (CA-CFAR) detector that uses local minimum of cells in sub-reference windows (SRW) and then it uses the general cell averaging technique to detect the target. Sub-reference sliding windows have been selected among reference cells in both sides of the test cell. We have improved the results obtained from the method of minimum selected cell averaging (MSCA)-CFAR [1] in the situations in which the distance between adjacent targets in the reference window is proportional to the length of SRW. This novel CFAR detector has been analyzed under Swerling II target fluctuating model, and compared with traditional cell averaging (CA) and minimum selected cell averaging (MSCA)-CFAR detectors. The simulation results indicate that, when the distance between adjacent targets in range cells equals to the length of the sub-reference windows, the local minimum selected cell averaging (LMSCA)-CFAR detector will provide more robust detection performance than CA — and MSCA-CFAR in homogeneous background with strong interfering targets.