A Radar Signal Deinterleaving Method Based on Complex Network and Laplacian Graph Clustering

IF 3.2 2区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Signal Processing Letters Pub Date : 2024-09-16 DOI:10.1109/LSP.2024.3461656

Qiang Guo;Shuai Huang;Liangang Qi;Daren Li;Mykola Kaliuzhnyi

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引用次数: 0

Abstract

Radar signal deinterleaving is an essential step in perceiving the battlefield situation and mastering military initiative in the information battlefield. Complex radar systems are rapidly updated and iterated, which exacerbates the possibility of “increasing batch” and “mistaken batch” during radar signal deinterleaving. In this letter, a novel method based on complex networks and Laplacian graph clustering is proposed to improve the accuracy of deinterleaving. First, a complex network is constructed to mine the spatial correlation relationships of the same radar signals. Then, based on the graph characteristics of the Laplacian matrix, the number of cluster centers is solved. Finally, this letter employs Laplacian spectral clustering based on graph segmentation to accomplish radar signal deinterleaving. The results of the experimental simulation demonstrate that the method is capable of effectively tackling the “increasing batch” and “mistaken batch” problems of radar signal deinterleaving, and could reach 99.88% deinterleaving accuracy with high robustness.

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基于复杂网络和拉普拉斯图聚类的雷达信号去交织方法

雷达信号解交织是信息战场上感知战场态势、掌握军事主动权的必要步骤。复杂雷达系统更新迭代速度快，加剧了雷达信号解交织过程中 "增批 "和 "误批 "的可能性。本文提出了一种基于复杂网络和拉普拉斯图聚类的新方法，以提高解交织的准确性。首先，构建复杂网络来挖掘相同雷达信号的空间相关关系。然后，根据拉普拉斯矩阵的图特征，求解聚类中心的数量。最后，本文采用基于图分割的拉普拉斯谱聚类来完成雷达信号的去交织。实验仿真结果表明，该方法能有效解决雷达信号解交织中的 "增批 "和 "错批 "问题，解交织精度可达 99.88%，且鲁棒性高。

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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来源期刊

IEEE Signal Processing Letters 工程技术-工程：电子与电气

CiteScore

7.40

自引率

12.80%

发文量

339

审稿时长

2.8 months

期刊介绍： The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing. Papers published in the Letters can be presented within one year of their appearance in signal processing conferences such as ICASSP, GlobalSIP and ICIP, and also in several workshop organized by the Signal Processing Society.