摘要： 为了识别复杂新体制的正交频分复用（OFDM）雷达信号，构造了一种基于相关性的快速滤波自适应提升（Fast Correlation-Based Filter Adaptive Boosting， FCBF-AdaBoost）联合算法，并结合了频域分析法的雷达信号识别方法。通过对频域幅值属性集进行离散化预处理后，该联合算法首先对输入的频域数据中冗余和不相关的幅值数据进行筛选并剔除，构成降维后的频域子集，再通过一种基于弱分类器集成的算法进行数据特征学习，最终通过大量雷达数据进行训练模型，实现对雷达信号的分类。理论分析验证了该算法的可行性，通过仿真实验看出，在各信噪比下，所提出的算法对OFDM雷达信号识别的准确率随着信噪比的增加明显提高，可达到94%以上。

中图分类号：TP391 文献标志码：A DOI: 10.16157/j.issn.0258-7998.256673
中文引用格式： 郭建，陈红. 基于FCBF和AdaBoost算法的OFDM雷达信号识别[J]. 电子技术应用，2026，52(1)：107-110.
英文引用格式： Guo Jian，Chen Hong. OFDM radar signal recognition based on FCBF and AdaBoost algorithm[J]. Application of Electronic Technique，2026，52(1)：107-110.

OFDM radar signal recognition based on FCBF and AdaBoost algorithm

Abstract： In order to identify the OFDM radar signals of complex new systems, a united algorithm based on Fast Correlation-Based Filter Adaptive Boosting (FCBF-AdaBoost) and a radar signal identification method based on frequency domain analysis are constructed. After discretizing the frequency domain amplitude attribute set, the joint algorithm firstly filters and rejects the redundant and uncorrelated amplitude data of the input frequency domain data to form a frequency-domain subset after dimension reduction. Then, the data feature learning is carried out through the algorithm of weak classifier integration, and finally the model is trained through a large amount of radar data to realize the classification of the radar signals. The feasibility of the algorithm is verified by theoretical analysis. It is shown by simulation experiments at various SNR that the proposed algorithm can significantly improve the accuracy of OFDM radar signal recognition with the increase of SNR. The accuracy of recognition can reach more than 94%.

Key words : OFDM radar signal recognition；fast correlation-based filter （FCBF）；weak classifier；adaptive boosting （AdaBoost）；frequency domain analysis