一种改进的基于Wigner分布的信号识别算法

Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869) Pub Date : 2004-04-20 DOI:10.1109/UT.2004.1405469

Fu-Sheng Lu, Cheng Yang, Pai-Ling Lin

{"title":"一种改进的基于Wigner分布的信号识别算法","authors":"Fu-Sheng Lu, Cheng Yang, Pai-Ling Lin","doi":"10.1109/UT.2004.1405469","DOIUrl":null,"url":null,"abstract":"A new modified Wigner distribution, in which the cumbersome cross-terms can be totally eliminated, is combined with the wavelet packet decomposition to get a better time-frequency analysis algorithm. The non-stationary signal are first decomposed into approximation and detail signals by the wavelet packet analysis, and then each constituent signal is analyzed by the modified distribution to get a time-frequency representation data matrix. To simplify the computation for identification, the Karhunen-Loe/spl grave/ve transform is used to find the principal eigenvector of the distribution data matrix. The principal eigenvectors of the approximation and detail signals construct the signal feature database for identification. In addition to numerical simulations, experiments of some underwater acoustic signal identification are conducted.","PeriodicalId":437450,"journal":{"name":"Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An improved Wigner distribution based algorithm for signal identification\",\"authors\":\"Fu-Sheng Lu, Cheng Yang, Pai-Ling Lin\",\"doi\":\"10.1109/UT.2004.1405469\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new modified Wigner distribution, in which the cumbersome cross-terms can be totally eliminated, is combined with the wavelet packet decomposition to get a better time-frequency analysis algorithm. The non-stationary signal are first decomposed into approximation and detail signals by the wavelet packet analysis, and then each constituent signal is analyzed by the modified distribution to get a time-frequency representation data matrix. To simplify the computation for identification, the Karhunen-Loe/spl grave/ve transform is used to find the principal eigenvector of the distribution data matrix. The principal eigenvectors of the approximation and detail signals construct the signal feature database for identification. In addition to numerical simulations, experiments of some underwater acoustic signal identification are conducted.\",\"PeriodicalId\":437450,\"journal\":{\"name\":\"Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UT.2004.1405469\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UT.2004.1405469","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

摘要

将一种新的改进Wigner分布与小波包分解相结合，得到了一种更好的时频分析算法，消除了Wigner分布中繁琐的交叉项。首先通过小波包分析将非平稳信号分解为近似信号和细节信号，然后对每个组成信号进行修正分布分析，得到时频表示数据矩阵。为了简化识别计算，采用Karhunen-Loe/spl grave/ve变换求分布数据矩阵的主特征向量。逼近信号和细节信号的主特征向量构成信号特征库，用于识别。在数值模拟的基础上，对部分水声信号进行了识别实验。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

An improved Wigner distribution based algorithm for signal identification

A new modified Wigner distribution, in which the cumbersome cross-terms can be totally eliminated, is combined with the wavelet packet decomposition to get a better time-frequency analysis algorithm. The non-stationary signal are first decomposed into approximation and detail signals by the wavelet packet analysis, and then each constituent signal is analyzed by the modified distribution to get a time-frequency representation data matrix. To simplify the computation for identification, the Karhunen-Loe/spl grave/ve transform is used to find the principal eigenvector of the distribution data matrix. The principal eigenvectors of the approximation and detail signals construct the signal feature database for identification. In addition to numerical simulations, experiments of some underwater acoustic signal identification are conducted.

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

Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869)

自引率

0.00%

发文量