有限相关环境下时变瞬时频率的建模

R. K. Pally, A. Beex
{"title":"有限相关环境下时变瞬时频率的建模","authors":"R. K. Pally, A. Beex","doi":"10.1109/ICDSP.2009.5201085","DOIUrl":null,"url":null,"abstract":"A TVAR model has been shown to perform well when applied to short data records for Instantaneous Frequency (IF) estimation of frequency modulated (FM) components in white noise. However, when the model is applied to a signal containing a finitely correlated signal in addition to the white noise, estimation performance degrades; especially when the correlated signal is not weak relative to the FM components. We extend the time-varying autoregressive (TVAR) model-based IF estimation for a finitely correlated environment by introducing a decorrelation delay larger than one between the time-varying coefficients. Comparison of the decorrelating TVAR based IF estimator to a conventional TVAR based IF estimator reveals performance gains at moderate to high signal to FM component power ratios.","PeriodicalId":409669,"journal":{"name":"2009 16th International Conference on Digital Signal Processing","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Modeling of time-varying Instanteous Frequency in a finitely correlated environment\",\"authors\":\"R. K. Pally, A. Beex\",\"doi\":\"10.1109/ICDSP.2009.5201085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A TVAR model has been shown to perform well when applied to short data records for Instantaneous Frequency (IF) estimation of frequency modulated (FM) components in white noise. However, when the model is applied to a signal containing a finitely correlated signal in addition to the white noise, estimation performance degrades; especially when the correlated signal is not weak relative to the FM components. We extend the time-varying autoregressive (TVAR) model-based IF estimation for a finitely correlated environment by introducing a decorrelation delay larger than one between the time-varying coefficients. Comparison of the decorrelating TVAR based IF estimator to a conventional TVAR based IF estimator reveals performance gains at moderate to high signal to FM component power ratios.\",\"PeriodicalId\":409669,\"journal\":{\"name\":\"2009 16th International Conference on Digital Signal Processing\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 16th International Conference on Digital Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDSP.2009.5201085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 16th International Conference on Digital Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSP.2009.5201085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

TVAR模型在白噪声条件下对调频(FM)分量的瞬时频率(IF)估计具有良好的应用效果。然而,当该模型应用于除白噪声外还含有有限相关信号的信号时,估计性能下降;特别是当相关信号相对于调频分量不弱时。我们通过在时变系数之间引入大于1的去相关延迟,扩展了基于时变自回归(TVAR)模型的有限相关环境中频估计。将去相关的基于TVAR的中频估计器与传统的基于TVAR的中频估计器进行比较,可以发现中高信号与调频分量功率比下的性能增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling of time-varying Instanteous Frequency in a finitely correlated environment
A TVAR model has been shown to perform well when applied to short data records for Instantaneous Frequency (IF) estimation of frequency modulated (FM) components in white noise. However, when the model is applied to a signal containing a finitely correlated signal in addition to the white noise, estimation performance degrades; especially when the correlated signal is not weak relative to the FM components. We extend the time-varying autoregressive (TVAR) model-based IF estimation for a finitely correlated environment by introducing a decorrelation delay larger than one between the time-varying coefficients. Comparison of the decorrelating TVAR based IF estimator to a conventional TVAR based IF estimator reveals performance gains at moderate to high signal to FM component power ratios.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信