P. Sun, Gengxin Zhang, Dexin Qu, Hui Ji, Hengheng Guo
{"title":"Cross Ambiguity Function Interpolation Algorithm for FDOA Estimation of Signal Location","authors":"P. Sun, Gengxin Zhang, Dexin Qu, Hui Ji, Hengheng Guo","doi":"10.1109/ICCSN.2019.8905267","DOIUrl":null,"url":null,"abstract":"The accuracy of the frequency difference of arrival (FDOA) estimation of signal location with the traditional cross ambiguity function (CAF) method is limited by the spectral resolution of CAF. This paper proposes a cross ambiguity function interpolation (CAFI) method, which uses linear interpolation of the phase difference of adjacent CAF values between frequency bins around CAF peak to estimate the FDOA. Theoretical analysis and Monte Carlo simulation results show that the accuracy of the proposed CAFI for FDOA estimation method has been significantly improved and it is close to Cramer-Rao Lower Bound (CRLB). In the case of a signal-to-noise ratio(SNR) of 5 dB and a data length of 128, the FDOA's estimated Root Mean Square Error (RMSE) is reduced to 5% of the conventional CAF direct result, and the estimation accuracy is improved by 20 times.","PeriodicalId":330766,"journal":{"name":"2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSN.2019.8905267","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The accuracy of the frequency difference of arrival (FDOA) estimation of signal location with the traditional cross ambiguity function (CAF) method is limited by the spectral resolution of CAF. This paper proposes a cross ambiguity function interpolation (CAFI) method, which uses linear interpolation of the phase difference of adjacent CAF values between frequency bins around CAF peak to estimate the FDOA. Theoretical analysis and Monte Carlo simulation results show that the accuracy of the proposed CAFI for FDOA estimation method has been significantly improved and it is close to Cramer-Rao Lower Bound (CRLB). In the case of a signal-to-noise ratio(SNR) of 5 dB and a data length of 128, the FDOA's estimated Root Mean Square Error (RMSE) is reduced to 5% of the conventional CAF direct result, and the estimation accuracy is improved by 20 times.