A New CFAR Detection Algorithm Based on Sorting Selection for Vehicle Millimeter Wave Radar

In this paper, a CFAR detection algorithm based on sorting selection is proposed for the vehicle millimeter wave radar in the actual detection. The principle of this algorithm is derived from the mean class CFAR and the ordered selection class (OS) CFAR algorithm. First, CA-CFAR and SO-CFAR are simulated and detected in the presence of extended range targets, and it is found that the detection performance can be improved by changing the protection unit. At the same time, the proposed method was tested and compared under the same conditions. Results show that although the detection performances of CA and SO-CFAR can be improved by increasing the number of protection units, they are not suitable for practical applications. However, the proposed method not only has no need for protection units but also has better detection performance. Then, CA-CFAR, SO-CFAR and the new algorithm are verified and compared using the real data obtained by a stationary vehicle. Results show that the detection performance of the proposed CFAR algorithm is significantly better than that of others. Finally, the new algorithm is tested in the case of self-driving motion. The measured data of three time points are selected for detection. The new CFAR algorithm can detect the target of interest in the distance dimension, which proves the feasibility of the algorithm.