Key Radar Signal Sorting and Recognition Method Based on Clustering Combined PRI transform Algorithm

Kaige Kang, Yixiao Zhang, Wenpu Guo, Luogeng Tian
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引用次数: 2

Abstract

In this paper, we investigate the problem of key radar signal sorting and recognition in electronic intelligence (ELINT). Our major contribution is the development of a combined approach based on clustering and PRI transform algorithm, to solve the problem that the traditional methods based on Pulse Description Words (PDW) were not exclusively targeted at tiny particular signals and, less time-efficient. We achieve this in three steps: firstly, PDW presorting is carried out by the DBSCAN clustering algorithm, then, PRI estimates of each cluster are obtained by the PRI transformation algorithm, finally, by judging the matching between various PRI estimates and key targets, it is determined whether the current signal contains key target signals or not. Simulation results show that the proposed method should improve the time efficiency of key signal recognition and deal with the complex signal environment with noise interference and overlapping signals.
基于聚类结合PRI变换算法的关键雷达信号分类识别方法
本文研究了电子情报(ELINT)中关键雷达信号的分类与识别问题。我们的主要贡献是开发了一种基于聚类和PRI变换算法的组合方法,解决了基于脉冲描述词(PDW)的传统方法不能专门针对微小的特定信号和时间效率较低的问题。我们分三步实现:首先通过DBSCAN聚类算法对PDW进行预排序,然后通过PRI变换算法得到各聚类的PRI估计,最后通过判断各PRI估计与关键目标的匹配程度来判断当前信号中是否包含关键目标信号。仿真结果表明,该方法能有效地提高关键信号识别的时间效率,并能很好地处理存在噪声干扰和信号重叠的复杂信号环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
8.70
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