无线电工程2024，Vol.54Issue(1)：78-88,11.DOI:10.3969/j.issn.1003-3106.2024.01.011
基于小波阈值去噪与时频图像检测的信号调制识别技术
Signal Modulation Recognition Based on Wavelet Threshold Denoising and Time-frequency Image Detection
摘要
Abstract
With the increasing complexity of communication environments,signal modulation recognition has become increasingly important.A modulation recognition method is proposed based on wavelet threshold denoising and time-frequency image detection to address the difficulty of digital signal modulation recognition at low signal-to-noise ratios.The method firstly converts the received real signal into an analytical signal and then denoises the analytical signal by the wavelet threshold method.Then the time-frequency reassignment technology is introduced to convert the denoised one-dimensional signal into a two-dimensional time-frequency image,and bilinear interpolation is used to scale the image to obtain a time-frequency image adapted to the size of the network input.Finally,the time-frequency map is input into the VGG network for training and recognition.The experimental results show that the proposed modulation recognition method performs well for modulation recognition under low signal to noise ratio.关键词
数字信号调制识别/时频分析/卷积神经网络Key words
digital signal modulation recognition/time-frequency analysis/convolutional neural network分类
信息技术与安全科学引用本文复制引用
孙思燕,张伟雄,唐娉,郑柯,张正..基于小波阈值去噪与时频图像检测的信号调制识别技术[J].无线电工程,2024,54(1):78-88,11.基金项目
国家自然科学基金(42192584)National Natural Science Foundation of China(42192584) （42192584）
