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Radar signals clustering based on spectrum atom decomposition and kernel method

机译:基于谱原子分解和核方法的雷达信号聚类

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The recognition and parameters estimation of radar emitter signals are crucial techniques in signal processing of Electronic Intelligence. In this paper, a new method of radar emitter signals recognition and parameters estimation based on time-frequency atom is proposed, which is by introduced into the idea of non-orthogonal decomposition of signals. Firstly, a new dictionary of spectrum atoms is proposed to decompose the signals by using Marching Pursuit based on FFT. Then the atoms characteristics vector can be achieved according to the parameters of decomposed atoms. Finally, the kernelized clustering algorithm is applied to identify radar emitter signals automatically and estimate parameters. Experiment results show that the proposed approach can obtain high accurate recognition rate and accurate parameters estimation result, it is feasible to realize in engineering.
机译:雷达发射器信号的识别和参数估计是电子情报信号处理中的关键技术。提出了一种基于时频原子的雷达辐射源信号识别和参数估计的新方法,并将其引入信号的非正交分解思想。首先,提出了一种新的谱原子字典,通过基于FFT的行进追踪算法对信号进行分解。然后可以根据分解后的原子参数获得原子特征向量。最后,采用核聚类算法自动识别雷达发射器信号并估计参数。实验结果表明,该方法可以获得较高的识别率和准确的参数估计结果,在工程上是可行的。

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