Anchalee Puengnim, N. Thomas, J. Tourneret, Herve Guillon
{"title":"Classification of GMSK signals with different bandwidths","authors":"Anchalee Puengnim, N. Thomas, J. Tourneret, Herve Guillon","doi":"10.1109/ICASSP.2008.4518034","DOIUrl":null,"url":null,"abstract":"This paper studies a Bayesian classifier which recognizes Gaussian minimum shift keying (GMSK) modulated signals with different bandwiths. We focus on identifying two different GMSK signals with BT = 0.25 and BT = 0.5 standardized by the consultative committee for space data system (CCSDS) for future space missions. The main idea of the proposed classifier is to compute the posterior probability of the observation sequence given each possible model by a modified Baum-Welch (BW) algorithm. The received GMSK signals are then classified according to the maximum a posteriori (MAP) rule.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2008.4518034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper studies a Bayesian classifier which recognizes Gaussian minimum shift keying (GMSK) modulated signals with different bandwiths. We focus on identifying two different GMSK signals with BT = 0.25 and BT = 0.5 standardized by the consultative committee for space data system (CCSDS) for future space missions. The main idea of the proposed classifier is to compute the posterior probability of the observation sequence given each possible model by a modified Baum-Welch (BW) algorithm. The received GMSK signals are then classified according to the maximum a posteriori (MAP) rule.