Bo Cheng, Cailian Chen, Zhezhuang Xu, Haoran Li, X. Guan
{"title":"基于无线传感器网络的声源定位:一种GCC-GA方法","authors":"Bo Cheng, Cailian Chen, Zhezhuang Xu, Haoran Li, X. Guan","doi":"10.1109/WOWMOM.2010.5534950","DOIUrl":null,"url":null,"abstract":"It is a very important and challenging task to localize an audio-source in wireless sensor networks (WSNs). One of efficient methods for audio-source localization is the so-called time difference of arrival (TDOA) based approach. In this paper, we propose a novel localization method based on Generalized Cross Correlation-Genetic Algorithm (GCC-GA). It utilizes GCC method to calculate the TDOA and GA to improve the localization accuracy. The proposed method is implemented in a real grid wireless sensor network. The experimental results show that the network can estimate the source location with better accuracy and lower complexity.","PeriodicalId":384628,"journal":{"name":"2010 IEEE International Symposium on \"A World of Wireless, Mobile and Multimedia Networks\" (WoWMoM)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Wireless sensor networks based localization for audio-source: A GCC-GA method\",\"authors\":\"Bo Cheng, Cailian Chen, Zhezhuang Xu, Haoran Li, X. Guan\",\"doi\":\"10.1109/WOWMOM.2010.5534950\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is a very important and challenging task to localize an audio-source in wireless sensor networks (WSNs). One of efficient methods for audio-source localization is the so-called time difference of arrival (TDOA) based approach. In this paper, we propose a novel localization method based on Generalized Cross Correlation-Genetic Algorithm (GCC-GA). It utilizes GCC method to calculate the TDOA and GA to improve the localization accuracy. The proposed method is implemented in a real grid wireless sensor network. The experimental results show that the network can estimate the source location with better accuracy and lower complexity.\",\"PeriodicalId\":384628,\"journal\":{\"name\":\"2010 IEEE International Symposium on \\\"A World of Wireless, Mobile and Multimedia Networks\\\" (WoWMoM)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Symposium on \\\"A World of Wireless, Mobile and Multimedia Networks\\\" (WoWMoM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WOWMOM.2010.5534950\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Symposium on \"A World of Wireless, Mobile and Multimedia Networks\" (WoWMoM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOWMOM.2010.5534950","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wireless sensor networks based localization for audio-source: A GCC-GA method
It is a very important and challenging task to localize an audio-source in wireless sensor networks (WSNs). One of efficient methods for audio-source localization is the so-called time difference of arrival (TDOA) based approach. In this paper, we propose a novel localization method based on Generalized Cross Correlation-Genetic Algorithm (GCC-GA). It utilizes GCC method to calculate the TDOA and GA to improve the localization accuracy. The proposed method is implemented in a real grid wireless sensor network. The experimental results show that the network can estimate the source location with better accuracy and lower complexity.