基于支持向量聚类的多分量线性调频信号检测
doi: 10.3724/SP.J.1146.2006.00617
Multi-component Linear FM Signal Detection Based on Support Vector Clustering
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摘要: 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。Abstract: 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.
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