Multicomponent Linear FM Signal Detection Based on Support Vector Clustering

Wang Linghuan, Ma Hongguang, Li Qi, Li Zheng
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引用次数: 3

Abstract

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
基于支持向量聚类的多分量线性调频信号检测
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,得到信号中峰值的个数,实现对LFM信号分量的检测。同时,提出了一种近似零均值的方法来减少SVC输入数据集的点数,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 -氡时频方法对于多分量LFM信号的检测和参数估计是有效的
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