Two-level CFAR Algorithm for Target Detection in MmWave Radar
Chuanwen Xu, Fenggui Wang, Yanbo Zhang, Xu Li, Mingshun Ai, Guang Yan
Abstract
In the classical Constant False Alarm Rate (CFAR) algorithms, each cell participates in the calculation of the background power many times, which leads to low computational efficiency. This paper proposes a two-level CFAR detection algorithm–Order Statistic Convolution-based Cell Averaging CFAR (OSCCA-CFAR) for target detection. The first level CFAR uses the order statistic CFAR (OS-CFAR) algorithm to pre-detect the targets in the distance-dimension of the Range-Doppler Matrix (RDM); Based on the equivalence relationship between convolution and sliding window structure, the second level CFAR detects targets in Doppler-dimension by using convolution-based cell averaging CFAR (CCA-CFAR). Experimental results in mmwave radar imaging show that the proposed algorithm can effectively improve the efficiency of target detection without affecting the detection results.