电讯技术2026，Vol.66Issue(1)：30-37,8.DOI:10.20079/j.issn.1001-893x.240808003
基于联合ICA和CNN的时频重叠信号识别
Recognition of Time-Frequency Overlapping Signals Based on Joint ICA and CNN
摘要
Abstract
Due to the openness of wireless communication channels,communication signals are easily affected by various natural or artificial interferences during transmission.Communication signals and interference signals are intertwined to form time-frequency overlapping signals.Under low interference-to-signal ratio conditions,traditional signal recognition methods perform poorly.To address this problem,based on the independent component analysis(ICA)algorithm and the convolutional neural network(CNN)with the channel attention mechanism(CA),a method for time-frequency overlapping signal recognition on ICA and CNN(OSR-IC)is proposed.This method uses the ICA algorithm to decompose the time-frequency overlapping signal into communication signals and interference signals,obtains the spectrum of the communication signal and the interference signal through fast Fourier transform,uses the two types of signal spectrum as the input of the CNN network,introduces the channel attention mechanism to obtain the weight of each channel,and then improves the network feature expression ability,and uses the improved CNN network to identify the interference signal.Simulation experiments show that when the interference-to-noise ratio is 0 dB,the proposed method can achieve a recognition rate of 94%or more for interference signals.关键词
干扰信号识别/时频重叠信号/独立成分分析/通道注意力机制/卷积神经网络Key words
interference signals identification/time-frequency overlapping signal/independent component analysis/channel attention mechanism/convolutional neural network分类
信息技术与安全科学引用本文复制引用
周尚聪,张勇,李东芳,张钟浩,王柳..基于联合ICA和CNN的时频重叠信号识别[J].电讯技术,2026,66(1):30-37,8.基金项目
国家重点研发计划(2021YFB2900404) （2021YFB2900404）
