Radar Target Recognition of Individuals Based on XGBoost

Radar target individual recognition refers to identifying individual targets by analyzing the target echo signals received by the radar. Due to the complexity and diversity of radar target individual characteristics, it is difficult to describe the changing patterns of these characteristics accurately with mathematical expressions. To address this issue, this paper proposes a radar target individual recognition method based on the XGBoost model, which processes the radar target signals, constructs feature vectors based on frequency spectra, and performs classification recognition. Experimental results demonstrate that the XGBoost-based radar target individual recognition method achieves good performance on this problem.