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Multicomponent Linear FM Signal Detection Based on Support Vector Clustering

机译:基于支持向量聚类的多分量线性调频信号检测

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摘要

The support vector clustering (SVC) algorithm was introduced to get the number of the pinnacles in the result of the time-frequency analysis and Radon transform of the multicomponent linear FM (LFM) signal, and to fulfil the detection of the components of the LFM signal. Meanwhile, an approach called near zero mean, for reducing the point number of the input data-set for SVC, was proposed to improve the computation efficiency. And a novel cluster labeling method was 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
机译:引入支持向量聚类(SVC)算法,对多分量线性调频(LFM)信号进行时频分析和Radon变换后得到尖峰数目,并完成对LFM分量的检测。信号。同时,为减少SVC的输入数据集的点数,提出了一种称为接近零均值的方法,以提高计算效率。并提出了一种新的聚类标记方法来改进SVC算法。仿真结果表明,SVC-rad-时频方法可有效检测多分量LFM信号并进行参数估计。

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