Modern Defense Technology ›› 2025, Vol. 53 ›› Issue (1): 120-128.DOI: 10.3969/j.issn.1009-086x.2025.01.013

• TARGET CHARACTERISTIC, DETECTION AND TRACKING TECHNOLOGY • Previous Articles     Next Articles

A Method of Working Mode Recognition for Multi-function Radar Based on RGCN

Chunlai YU1, Mingyue FENG1, Hongbin JIN1, Fuqun ZHANG1, Qiangfei ZHANG2   

  1. 1.Air Force Early Warning Academy,Wuhan 430019,China
    2.PLA 95865 Troops,Beijing 102218,China
  • Received:2023-10-17 Revised:2024-01-23 Online:2025-02-28 Published:2025-02-27

一种基于RGCN的多功能雷达工作模式识别方法

郁春来1, 冯明月1, 金宏斌1, 张福群1, 张强飞2   

  1. 1.中国人民解放军空军预警学院,湖北 武汉 430019
    2.中国人民解放军95865部队,北京 102218
  • 作者简介:郁春来(1981-),男,江苏涟水人。教授,博士,研究方向为电子对抗信息处理。

Abstract:

Multi-function radar has gained widespread application due to its flexible working modes, agile waveform characteristics, and ability to perform multiple tasks in parallel. However, these capabilities also pose significant challenges to radar intelligence reconnaissance and countermeasures. Recognizing the working modes of multi-function radar serves as a fundamental step for subsequent threat assessment, adaptive countermeasures, and guided attacks, directly influencing the specificity and effectiveness of radar countermeasures. In this paper, a novel method for recognizing the working modes of multi-function radar, leveraging relational graph convolutional networks (RGCNs) is proposed. By analyzing the various working modes of multi-function radar, the method enables parallel data processing and addresses the interactions between different working modes and their characteristic parameters.

Key words: multi-function radar, working mode recognition, neural network, graph convolution network, graph convolution network

摘要:

多功能雷达因其灵活的工作模式和捷变的波形特征,可并行执行多种任务等优势,已获得广泛应用,对雷达情报侦察对抗带来了极大挑战。识别多功能雷达工作模式是后续威胁评估、自适应对抗和引导攻击的前提和基础,直接决定着雷达对抗措施的针对性和有效性。主要以典型多功能雷达为研究对象,对典型的作战场景仿真建模,在深入分析多功能雷达不同工作模式的基础上,提出了一种基于关系图卷积网络(relational graph convolutional networks,RGCN)的多功能雷达工作模式识别的新方法,实现了数据的并行化处理,解决了不同工作模式与特征参数之间的相互作用。

关键词: 多功能雷达, 工作模式识别, 神经网络, 图卷积网络, 关系图卷积网络

CLC Number: