{"title":"A Signal Blind Detection Method Based on Wavelet Denoising","authors":"Yue Guo, Bin Wang","doi":"10.1109/ITNEC48623.2020.9084728","DOIUrl":null,"url":null,"abstract":"In this paper, a blind detection method is proposed based on wavelet denoising for short burst signals under low SNR (Signal-to-Noise Ratio), and a definite method to determine the decision threshold is given. The method first performs wavelet denoising on the received data, and then uses the energy detector based on a short window to detect the existence of the signal. Simulation results show that for 2FSK, MSK, QPSK and 16QAM signals, when SNR is −12dB, the detection probability can be higher than 85% and false alarm probability is basically maintained below 20%.","PeriodicalId":235524,"journal":{"name":"2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITNEC48623.2020.9084728","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a blind detection method is proposed based on wavelet denoising for short burst signals under low SNR (Signal-to-Noise Ratio), and a definite method to determine the decision threshold is given. The method first performs wavelet denoising on the received data, and then uses the energy detector based on a short window to detect the existence of the signal. Simulation results show that for 2FSK, MSK, QPSK and 16QAM signals, when SNR is −12dB, the detection probability can be higher than 85% and false alarm probability is basically maintained below 20%.