在混响环境中跟踪声源的粒子滤波算法

D. Ward, E. Lehmann, R. C. Williamson
{"title":"在混响环境中跟踪声源的粒子滤波算法","authors":"D. Ward, E. Lehmann, R. C. Williamson","doi":"10.1109/TSA.2003.818112","DOIUrl":null,"url":null,"abstract":"Traditional acoustic source localization algorithms attempt to find the current location of the acoustic source using data collected at an array of sensors at the current time only. In the presence of strong multipath, these traditional algorithms often erroneously locate a multipath reflection rather than the true source location. A recently proposed approach that appears promising in overcoming this drawback of traditional algorithms, is a state-space approach using particle filtering. In this paper we formulate a general framework for tracking an acoustic source using particle filters. We discuss four specific algorithms that fit within this framework, and demonstrate their performance using both simulated reverberant data and data recorded in a moderately reverberant office room (with a measured reverberation time of 0.39 s). The results indicate that the proposed family of algorithms are able to accurately track a moving source in a moderately reverberant room.","PeriodicalId":13155,"journal":{"name":"IEEE Trans. Speech Audio Process.","volume":"83 1","pages":"826-836"},"PeriodicalIF":0.0000,"publicationDate":"2003-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"358","resultStr":"{\"title\":\"Particle filtering algorithms for tracking an acoustic source in a reverberant environment\",\"authors\":\"D. Ward, E. Lehmann, R. C. Williamson\",\"doi\":\"10.1109/TSA.2003.818112\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional acoustic source localization algorithms attempt to find the current location of the acoustic source using data collected at an array of sensors at the current time only. In the presence of strong multipath, these traditional algorithms often erroneously locate a multipath reflection rather than the true source location. A recently proposed approach that appears promising in overcoming this drawback of traditional algorithms, is a state-space approach using particle filtering. In this paper we formulate a general framework for tracking an acoustic source using particle filters. We discuss four specific algorithms that fit within this framework, and demonstrate their performance using both simulated reverberant data and data recorded in a moderately reverberant office room (with a measured reverberation time of 0.39 s). The results indicate that the proposed family of algorithms are able to accurately track a moving source in a moderately reverberant room.\",\"PeriodicalId\":13155,\"journal\":{\"name\":\"IEEE Trans. Speech Audio Process.\",\"volume\":\"83 1\",\"pages\":\"826-836\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"358\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Trans. Speech Audio Process.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TSA.2003.818112\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Trans. Speech Audio Process.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TSA.2003.818112","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 358

摘要

传统的声源定位算法试图仅使用在当前时间从传感器阵列收集的数据来找到声源的当前位置。在强多径存在的情况下,这些传统算法往往会错误地定位多径反射而不是真实的源位置。最近提出的一种方法似乎有望克服传统算法的这一缺点,即使用粒子滤波的状态空间方法。在本文中,我们制定了一个使用粒子滤波器跟踪声源的一般框架。我们讨论了适合该框架的四种特定算法,并使用模拟混响数据和在中等混响办公室(测量混响时间为0.39秒)中记录的数据演示了它们的性能。结果表明,所提出的算法家族能够准确地跟踪中等混响房间中的移动源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Particle filtering algorithms for tracking an acoustic source in a reverberant environment
Traditional acoustic source localization algorithms attempt to find the current location of the acoustic source using data collected at an array of sensors at the current time only. In the presence of strong multipath, these traditional algorithms often erroneously locate a multipath reflection rather than the true source location. A recently proposed approach that appears promising in overcoming this drawback of traditional algorithms, is a state-space approach using particle filtering. In this paper we formulate a general framework for tracking an acoustic source using particle filters. We discuss four specific algorithms that fit within this framework, and demonstrate their performance using both simulated reverberant data and data recorded in a moderately reverberant office room (with a measured reverberation time of 0.39 s). The results indicate that the proposed family of algorithms are able to accurately track a moving source in a moderately reverberant room.
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:481959085
Book学术官方微信