Multi-Target Detection Based on Improved CA-CF AR Algorithm

Abstract

To solve the problem of target occlusion in the mean level (ML) constant false alarm rate (CFAR) algorithm under multi-target conditions, an improved cell averaging (CA)-CFAR algorithm is proposed in this paper. First, all the reference cells are divided equally. Then, the mean values of the adjacent sub-reference cells are processed by the ratio discrimination method, and when the ratio is not in the selected interval, the sub-reference cell with a larger mean value is assigned. Finally, a new detection threshold is obtained by calculating the mean value of all the sub-reference cells. Simulation and millimeter wave (mmWave) radar experiments show that, compared with CA-CFAR, the improved CA-CFAR algorithm effectively reduces the detection threshold of multi-target region and solves the problem of missing detection caused by mutual interference between multi-targets, which also proves the effectiveness of the proposed algorithm.