摘要
激光雷达辐射源个体识别时缺少对雷达信号离散型电子脉冲相位的考虑,导致识别准确率较低。对此,提出基于多源信息融合的激光雷达腐蚀个体识别方法。通过分析辐射源个体指纹产生机理,得知激光雷达辐射源信号个体产生差异的源头为相位噪声的影响。分析雷达辐射源信号的时频域特点,构建侦察机接收信号、恒波信号、脉冲信号、调频信号及相位编码信号的数学模型,基于上述模型在时频域上进行频率编码,并根据不同信号衰减能力的不同,对其进行权重赋值,构建雷达辐射源信号的综合模型。在信号模型的基础上采用多源信息融合算法,计算不同个体指纹的属性测度概率,实现辐射源个体识别。实验证明结果表明,所提方法在信噪比环境下的整体平均识别准确率大于90%,所用识别时间最长为50 s,具有实用性。
The recognition accuracy of individual lidar emitter is low due to the lack of consideration of discrete subpulse phase of radar signal.For this reason,a method of individual identification of laser radar corrosion based on multi-source information fusion is proposed.By analyzing the generation mechanism of individual fingerprint of radiation source,it is known that the source of individual difference of laser radar radiation source signal is the influence of phase noise.the time-frequency and frequency-domain characteristics of radar emitter signals are analyzed,the mathematical models of reconnaissance aircraft receiving signals,constant wave signals,pulse signals,FM signals and phase coded signals are constructed,and the frequency coding in time-frequency and frequency-domain based on the above models,and assign weights to them according to different signal attenuation capabilities,so as to build a comprehensive model of radar emitter signals.On the basis of the signal model,multi-source information fusion algorithm is used to calculate the attribute measure probability of different individual fingerprints to realize the individual identification of emitters.The experimental results show that the overall average recognition accuracy of the proposed method in the SNR environment is more than 90%,and the maximum recognition time is 50 seconds,which is practical.
作者
农忠海
陈雅
NONG Zhonghai;CHEN Ya(Guangxi Police College,Nanning 530000,China;NO.206 Doma-Dong 53-27,Seo-Gu,Daejeon 35337,Korea;Guangxi Key Laboratory of Human-machine Interaction and Intelligent Decision,Nanning 530001,China)
出处
《激光杂志》
CAS
北大核心
2023年第6期143-149,共7页
Laser Journal
基金
国家建设高水平大学公派研究生项目(No.202008450033)
广西高校中青年教师基础能力提升项目(No.2023KY0910)
广西人机交互与智能决策重点实验室资助。
关键词
多源信息融合
激光雷达
辐射源个体
识别方法
multi-source information fusion
lidar
individual radiation source
identification method
