Support Vector Clustering and Type-Entropy Based Radar Signal Sorting Method

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Support Vector Clustering and Type-Entropy Based Radar Signal Sorting Method

更新时间：2025-07-09

- Support Vector Clustering and Type-Entropy Based Radar Signal Sorting Method
- Vol. 44, Issue 8, Pages: 63-67(2010)
- 作者机构：
  
  1. 哈尔滨工程大学信息与通信工程学院,哈尔滨,150001
  2. 哈尔滨工业大学空间控制与惯性技术研究中心,哈尔滨,150001
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN974
- Online First：10 August 2010，
  
  Published：2010
- 稿件说明：
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Support Vector Clustering and Type-Entropy Based Radar Signal Sorting Method[J]. 2010, 44(8): 63-67.
DOI：

Support Vector Clustering and Type-Entropy Based Radar Signal Sorting Method[J]. 2010, 44(8): 63-67. DOI：

摘要

针对复杂环境下传统雷达信号分选处理中由于设定容差难以准确分选的问题

提出一种分层互耦支持向量聚类(SVC)联合类型熵识别的多参数雷达信号分选方法.该方法首先对雷达信号的全脉冲序列进行分层处理

再分别对每个子序列进行SVC聚类

然后引入分层耦合的思想

利用所提取子序列的全部质心

重新进行SVC聚类

将各分层的全脉冲序列中属于同一雷达信号源的子序列连接起来

从而实现对雷达全脉冲序列信号的分选.根据类型熵随信号种类数的增加及信号复杂性的增加而增大的特点

对多参数聚类结果进行类型熵的计算

并将类型熵识别用来辅助信号分选.实验结果表明

对于高脉冲密度环境和复杂的信号形式

提出的方法避免了传统信号分选方法中所面临的容差问题对信号分选的影响

可以实现有效分选.

Abstract

Focusing on the problem that the conventional radar signal sorting methods based on the tolerance are difficult to accurate sorting in complex and dense pulse environment of modern electronic warfare

a new sorting method is presented based on delaminating coupling and support vector clustering(SVC). All pulse sequences of radar signals are determined using delaminating processing and then each sub-sequence is separately processed by SVC clustering. Then the idea of delaminating coupling is introduced. And re-SVC clustering is determined by using all centroids of the extracted sub-sequences so that the sub-sequences which belong to the same radar emitter in all pulse sequences of the various layers are connected to achieve the radar full pulse sequence sorting. The character that type-entropy value is getting bigger with the increasing of categories and complexity of pulse signals is used to calculate type-entropy on the multi-parameters clustering results.The type-entropy recognition is used to assist signal sorting. Experimental results show that the system can efficiently sort radar signals in the complex pulses environment and avoid the impact on signal sorting for the tolerance problem in traditional signal sorting methods.

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references

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ZHANG Hongchang, RUAN Huailin, GONG Liangliang, et al. New clustering approach for sorting unknown radar emitter signal [J]. Computer Engineering and Applications, 2008, 44(27): 200-202.

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