电子科技大学学报2024，Vol.53Issue(2)：201-209,9.DOI:10.12178/1001-0548.2023096
基于频域数据压缩感知的复合调制信号盲识别
Blind Recognition for Composite Modulation Signal Based on Frequency-Domain Data Compressed Sensing
摘要
Abstract
Modern TT&C(Tracking,Telemetry and Command)system mostly adopts the composite modulation in a form of"pulse coding/multi-subcarrier internal modulation/external modulation".This complicated scheme brings great challenges to signal accurate recognition in the absence of prior information and low signal-to-noise ratio(SNR)scenario.The existing composite modulation blind recognition methods based on feature extraction and pattern recognition are sensitive to signal features and sample size,and the whole process becomes even more cumbersome in the case of multiple subcarriers.In this paper,based on the unified carrier system composite modulated signal modeling,a new idea of blind recognition is proposed to train and classify the compressed composite modulated signal frequency domain data by using the inverse residual packet convolutional structure of lightweight neural network.By means of experiment platform construction and Python code designing,the proposed method verification for 10 composite modulated signals in condition of various SNRs is implemented.The results show that the recognition accuracy of the proposed method can reach 94.5%(SNR=0 dB)and 100%(SNR=5 dB)respectively;moreover,the sample size required for equal recognition accuracy is less than the existing statistical features and decision tree-based methods,and both the performance and amount of neural networks parameters used for classification are better than those of the benchmark network.关键词
复合调制/盲识别/统一载波体制/频域数据/压缩感知/轻量化神经网络Key words
composite modulation/blind recognition/unified carrier scheme/frequency-domain data/compressed sensing/lightweight neural network分类
信息技术与安全科学引用本文复制引用
何羚,阳鹏飞,阎啸,钟旭诺,白泰礼..基于频域数据压缩感知的复合调制信号盲识别[J].电子科技大学学报,2024,53(2):201-209,9.基金项目
四川省自然科学基金面上项目(2022NSFSC0545) （2022NSFSC0545）
