LDACS系统基于循环谱和残差神经网络的频谱感知方法  

Spectrum sensing method based on cyclic spectrum and residual neural network in LDACS system

作　　者：王磊[1] 张劲 叶秋炫 WANG Lei;ZHANG Jin;YE Qiuxuan(Key Laboratory of Civil Aviation Flight Wide Area Surveillance and Security Control Technology,Civil Aviation University of China,Tianjin 300300,China)

机构地区：[1]中国民航大学民航航班广域监视与安全管控技术重点实验室,天津300300

出　　处：《系统工程与电子技术》2024年第9期3231-3238,共8页Systems Engineering and Electronics

基　　金：国家自然科学基金(U2233216);天津市多元投入基金(21JCQNJC00770);中国民航大学民航航班广域监视与安全管控技术重点实验室开放基金(202101)资助课题。

摘　　要：针对L波段数字航空通信系统(L-band digital aeronautic communication system,LDACS)可用频谱资源有限且易受大功率测距仪(distance measuring equipment,DME)信号干扰的问题,提出一种基于降维循环谱和残差神经网络的频谱感知方法。首先理论推导分析了DME信号的循环谱特征;然后利用Fisher判别率(Fisher discriminant rate,FDR)提取循环频率能量最大的向量,通过主成分分析(principal component analysis,PCA)进行预处理特征增强;最后给出数据处理后的循环谱向量与卷积神经网络相结合的实现过程,实现了DME信号的有效检测。仿真结果表明,该方法对噪声不敏感,当信噪比不低于-15 dB时,平均检测概率大于90%。当信噪比不低于-14 dB,检测概率接近100%。To solve the problem that the available spectrum resources of L-band digital aeronautic communication system(LDACS)are limited and vulnerable to interference from high-power distance measuring equipment(DME)signals,a spectrum sensing method based on reduced dimension cyclic spectrum and residual neural network is proposed.Firstly,the cyclic spectrum characteristics of DME signal are analyzed theoretically.Then Fisher discriminant rate(FDR)is used to extract the vector with the highest cycle frequency energy,and the pre-processing features are enhanced by principal component analysis(PCA).Finally,the process of combining the cyclic spectral vector and convolutional neural network after data processing is given,and the effective detection of DME signal is achieved.Simulation results show that the method is not sensitive to noise,and the average detection probability is greater than 90%when the signal-to-noise ratio is no less than-15 dB.When the signal-to-noise ratio is not less than-14 dB,the detection probability is close to 100%.

关 键 词：L波段数字航空通信系统 测距仪 频谱感知 循环谱 残差神经网络 

分 类 号：TN925[电子电信—通信与信息系统]