天波超视距雷达地海杂波图像增强与检测器设计

罗忠涛; 龚彦如; 黎霁萱; 卢琨

doi:10.12263/DZXB.20240403

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天波超视距雷达地海杂波图像增强与检测器设计

学术论文 | 更新时间：2025-12-11

- 天波超视距雷达地海杂波图像增强与检测器设计
  增强出版
- Land-Sea Clutter Image Enhancement and Detector Design for Sky-Wave Over-the-Horizon Radar
- 电子学报 2024年52卷第12期页码：4037-4047
- 作者机构：
  
  1.重庆邮电大学通信与信息工程学院，重庆 400065
  2.南京电子技术研究所，江苏南京 210013
- 作者简介：
  
  [ "罗忠涛男，1984年生.现为重庆邮电大学信息与通信工程学院副教授.主要研究方向为统计信号处理、数字图像处理与机器学习.E-mail: luozt@cqupt.edu.cn" ]
  [ "龚彦如女，1999年生.现为重庆邮电大学信息与通信工程学院在读硕士研究生.主要研究方向为雷达信号与图像处理.E-mail: 2602086151@qq.com" ]
  [ "黎霁萱女，2001年生.现为重庆邮电大学信息与通信工程学院在读硕士研究生.主要研究方向为信号处理与机器学习在雷达系统中的应用.E-mail: lijixuan0725@163.com" ]
  [ "卢琨男，1977年生.博士，研究员级高级工程师.主要研究方向为超视距雷达系统设计和信息处理.E-mail: mimimomoba@gmail.com" ]
- 基金信息：
  
  国家自然科学基金(62231006);重庆市教委科学技术研究项目(KJQN202300633)
- DOI：10.12263/DZXB.20240403
  中图分类号： TN958.93;
- 收稿：2024-05-07，
  
  修回：2024-09-29，
  
  纸质出版：2024-12-25
- 稿件说明：
移动端阅览
罗忠涛, 龚彦如, 黎霁萱, 等. 天波超视距雷达地海杂波图像增强与检测器设计[J]. 电子学报, 2024, 52(12): 4037-4047.

LUO Zhong-tao, GONG Yan-ru, LI Ji-xuan, et al. Land-Sea Clutter Image Enhancement and Detector Design for Sky-Wave Over-the-Horizon Radar[J]. Acta Electronica Sinica, 2024, 52(12): 4037-4047.
罗忠涛, 龚彦如, 黎霁萱, 等. 天波超视距雷达地海杂波图像增强与检测器设计[J]. 电子学报, 2024, 52(12): 4037-4047. DOI：10.12263/DZXB.20240403

LUO Zhong-tao, GONG Yan-ru, LI Ji-xuan, et al. Land-Sea Clutter Image Enhancement and Detector Design for Sky-Wave Over-the-Horizon Radar[J]. Acta Electronica Sinica, 2024, 52(12): 4037-4047. DOI：10.12263/DZXB.20240403

摘要

天波超视距雷达的效能受制于工作环境.当电离层状态不理想或雷达工作参数不适合，雷达信号无法照射预定区域.因此，地海杂波是否正常能够直接反映天波雷达的工作状态.针对天波雷达杂波信号样本匮乏和不均衡问题，本文提出基于生成对抗网络的杂波距离-多普勒图像数据增强方法，采用轻量化ResNet18实时识别雷达图像，进而设计地海杂波检测器，实现对地海杂波状态的自动识别.该检测器从距离-多普勒图中自动提取高幅度区域，通过增扩图集所训练的分类网络进行图像类别判断，并将结果反馈给雷达操作人员.仿真结果表明，本文的地海杂波数据增强将识别器的准确率提高了25.26%，地海杂波检测器能够准确判断实测数据和文献图像的杂波状态.因此，该检测器可作为天波雷达的扩展模块，自动检测和警报杂波异常状态，有利于提高天波雷达自动化程度.

Abstract

Sky-wave over-the-horizon radar (OTHR) effectiveness is limited by the operation environment. When the ionospheric state is bad or the operating parameters are unsuitable

the radar signal will not illuminate the scheduled area. Hence

the fact that the land-sea clutter (LSC) is normal or abnormal directly reflects the working status of OTHR. To address the scarcity and imbalance of OTHR clutter signals

a data enhancement method based on generative adversarial network is proposed for clutter range-Doppler image enhancement. A lightweight ResNet18 model is used for real-time identification of the radar images. Further

an LSC anomaly detector (LSCAD) is designed to achieve automatic identification of the radar LSC situation. The LSCAD extracts the high-amplitude region from the radar range-Doppler map

classifies it by the classification network based on the augmented dataset

and feds back to the radar operator. Simulation results show that the LSC data enhancement increases the LSC classifier accuracy by 25.26%. The LSCAD can make a correct judgement on the LSC status of the real data and literature images. Therefore

the LSCAD can be used as an extended module of the OTHR and provides automatic detection and warning about the LSC anomaly

which helps OTHR improving the degree of automation.

关键词

Keywords

references

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