基于支持向量聚类的多分量线性调频信号检测

为了精确获取多分量线性调频(Linear FM, LFM)信号中分量的数量，该文引入支持向量聚类(Support Vector Clustering, SVC)算法对LFM信号的Radon-时频分析结果进行聚类分析，完成多个分量的检测；并通过减少SVC算法中输入集样本数量和改进聚类标识方法为直接聚类标识法，提高了SVC算法的计算效率。仿真结果表明：在较低信噪比条件下，Radon-时频分析和SVC结合的方法可有效地检测多分量LFM信号中分量数和进行参数估计。

Multi-component Linear FM Signal Detection Based on Support Vector Clustering

The Support Vector Clustering (SVC) algorithm is introduced to get the number of the pinnacles in the result of the time-frequency analysis and Radon transform of the multi-component Linear FM (LFM) signal, and to finish the detection of the components of the LFM signal. Meanwhile, the preprocessing to reduce the points’ number of the input data-set for SVC is proposed to improve the computation efficiency. And a novel cluster labeling method is developed to improve the SVC algorithm. The simulation results depict that the SVC-Radon-time-frequency approach is efficient for the detection and parameter estimation of the multi-components LFM signal with low SNR.