Land-Sea Clutter Image Enhancement and Detector Design for Sky-Wave Over-the-Horizon Radar

LUO Zhong-tao; GONG Yan-ru; LI Ji-xuan; LU Kun

doi:10.12263/DZXB.20240403

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Land-Sea Clutter Image Enhancement and Detector Design for Sky-Wave Over-the-Horizon Radar

PAPERS | 更新时间：2025-12-11

- Land-Sea Clutter Image Enhancement and Detector Design for Sky-Wave Over-the-Horizon Radar
  增强出版
- ACTA ELECTRONICA SINICA Vol. 52, Issue 12, Pages: 4037-4047(2024)
- 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：
- 基金信息：
  
  National Natural Science Foundation of China(62231006);Scientific and Technological Research Program of Chongqing Municipal Education Commission(KJQN202300633)
- DOI：10.12263/DZXB.20240403
  CLC： TN958.93;
- Received：07 May 2024，
  
  Revised：2024-09-29，
  
  Published：25 December 2024
- 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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