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Research on Radar Signal Sorting Algorithm Based on Supervised Learning

机译:基于监督学习的雷达信号分类算法研究

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Aiming at the main sorting stage of known radar signals in the radar signal sorting system, using supervised learning algorithms in machine learning to replace the traditional sorting algorithms which based on pulse repetition interval. The experimental results show that the supervised learning algorithms can successfully sort overlapping multi-type radar pulse signals, and the sorting accuracy of some algorithms exceeded 95%. It is feasible to apply the supervised learning algorithm to the main sorting stage of known radar signals.
机译:针对雷达信号分类系统中已知雷达信号的主要分选阶段,在机器学习中使用监督学习算法来替换基于脉冲重复间隔的传统分类算法。 实验结果表明,监督学习算法可以成功排序重叠的多型雷达脉冲信号,一些算法的分类精度超过95%。 将监督学习算法应用于已知雷达信号的主分选阶段是可行的。

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