摘要
被动雷达在预警探测和低慢小目标(LSS)检测中具有重要作用。由于被动雷达信号辐射源不可控,目标特性更为复杂,导致检测和识别极其困难。该文构建了被动雷达低慢小探测数据集(LSS-PR-1.0),该数据集包含了直升机、无人机、快艇、客轮4种典型海空目标的雷达回波信号,以及低高海况的海杂波数据,为该领域研究提供了数据支撑。在目标特征提取和分析方面,首先采用奇异值分解海杂波抑制方法,去除海杂波强Bragg峰对目标回波的影响。在此基础上,提出4类10种多域特征提取和分析方法,包括时域特征(相对平均幅度)、频域特征(频谱特征、多普勒瀑布图、距离多普勒特征)、时频域特征、运动特征(航向差、航迹参数、速度变化区间、速度变异系数、加速度)等。基于实测数据对4种海空目标特性进行了对比分析,总结各类目标特性规律,为后续目标识别奠定了基础。
Passive radar plays an important role in early warning detection and Low Slow Small(LSS)target detection.Due to the uncontrollable source of passive radar signal radiations,target characteristics are more complex,which makes target detection and identification extremely difficult.In this paper,a passive radar LSS detection dataset(LSS-PR-1.0)is constructed,which contains the radar echo signals of four typical sea and air targets,namely helicopters,unmanned aerial vehicles,speedboats,and passenger ships,as well as sea clutter data at low and high sea states.It provides data support for radar research.In terms of target feature extraction and analysis,the singular-value-decomposition sea-clutter-suppression method is first adopted to remove the influence of the strong Bragg peak of sea clutter on target echo.On this basis,four categories of ten multi-domain feature extraction and analysis methods are proposed,including time-domain features(relative average amplitude),frequency-domain features(spectral features,Doppler waterfall plot,and range Doppler features),time-frequency-domain features,and motion features(heading difference,trajectory parameters,speed variation interval,speed variation coefficient,and acceleration).Based on the actual measurement data,a comparative analysis is conducted on the characteristics of four types of sea and air targets,summarizing the patterns of various target characteristics and laying the foundation for subsequent target recognition.
作者
陈小龙
饶桂林
关键
王金豪
王洪永
张财生
易建新
万显荣
饶云华
CHEN Xiaolong;RAO Guilin;GUAN Jian;WANG Jinhao;WANG Hongyong;ZHANG Caisheng;YI Jianxin;WAN Xianrong;RAO Yunhua(Naval Aviation University,Yantai 264001,China;School of Electronic Information,Wuhan University,Wuhan 430072,China)
出处
《雷达学报(中英文)》
北大核心
2025年第2期249-268,共20页
Journal of Radars
基金
国家自然科学基金(62222120,61931021,61931015)
山东省自然科学基金(ZR2024JQ003)。
关键词
低慢小目标
被动雷达
海杂波抑制
多域特征提取
特性分析
公开数据集
Low Slow Small(LSS)targets
Passive radar
Sea clutter suppression
Multi-domain feature extraction
Characterization
Publicly available datasets
