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作 者:刘人玮 查雄 李天昀[1] 章昕亮 龚佩 LIU Renwei;ZHA Xiong;LI Tianyun;ZHANG Xinliang;GONG Pei(Information System Engineering College,Information Engineering University,Zhengzhou 450001,China)
机构地区:[1]信息工程大学信息系统工程学院,郑州450001
出 处:《电讯技术》2024年第2期252-260,共9页Telecommunication Engineering
摘 要:现有跳频信号辐射源个体识别方法大多围绕跳变瞬态的特征进行讨论,其捕获和精准定位的难度较大。因此,提出了一种基于解调重构的跳频信号辐射源个体识别方法,能够有效利用跳频信号的稳态信息进行辐射源个体识别。首先对跳频信号进行跳变定时,提取出各跳的基带波形;然后解调出各跳的符号,并将其经过理想成型滤波器,得到理想的重构基带波形;最后将原始波形和重构波形一起送入神经网络,得到分类结果。给出发射机畸变模型和畸变参数范围,经过多次测试给出网络参数的建议取值范围,并进行验证实验。实验结果表明,该方法能够有效地完成跳频信号辐射源个体识别任务。Most of the existing methods for frequency hopping(FH)signal emitter identification focus on the characteristics of hopping transient time.However,the short transient time makes it difficult to capture and locate accurately.Therefore,a new method of emitter identification based on demodulation and reconstruction is proposed.This method can effectively use the steady-state information of FH signal for emitter identification.Firstly,the FH signal is timed to extract the baseband waveform of each hop.Then,the symbols of each hop are demodulated and passed through the ideal shaping filter to obtain the ideal reconstructed baseband waveform.Finally,the original waveform and the reconstructed waveform are sent to the neural network to get the classification results.The distortion model and parameters’range of the transmitter are given.After many tests,the recommended values range of network parameters are given,and the verification experiments are carried out.Experimental results show that this method can effectively complete the task of individual recognition of FH signal emitter.
分 类 号:TN971[电子电信—信号与信息处理]
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