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Radar emitter signal recognition based on time-frequency analysis

机译:基于时频分析的雷达辐射源信号识别

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The extraction of radar emitter identification is very important to distinct the correct target. Up to now, many corresponding methods are proposed. But most of it has the problems of low recognition rate and not adapting to low SNR environment. In the paper, a novel method is proposed. The approach utilizes time-frequency analysis methods and singular value distribution(SVD) to extract the singular values of signal, making it be the feature vector., and neural network based classifiers were designed to identify radar emitter signals automatically. The experimental results show that it can achieve a satisfying accurate recognition rate when signal-to-noise rate varies in a large range. It is proved to be valid and practical approach.
机译:雷达发射极识别的提取对于不同的靶标非常重要。到目前为止,提出了许多相应的方法。但大多数它具有低识别率并且不适应低SNR环境的问题。本文提出了一种新方法。该方法利用时频分析方法和奇异值分布(SVD)提取信号的奇异值,使其成为特征向量。并且设计神经网络的分类器自动识别雷达发射极信号。实验结果表明,当信噪比在大范围内变化时,它可以实现满足的准确识别率。被证明是有效和实用的方法。

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