{"title":"使用超宽带传感器网络定位多个无标签目标的简单方法","authors":"R. Zetik, Snezhana Jovanoska, R. Thoma","doi":"10.1109/ICUWB.2011.6058843","DOIUrl":null,"url":null,"abstract":"In this article we propose a low complexity algorithm for detection and localization of multiple targets using UWB sensor networks. We assume that the targets being tracked do not have any devices or tags attached. They are localized using scattered electromagnetic waves. Our envisaged sensor network consists of sensor nodes that can autonomously detect and localize the closest target. Those partial location estimates are mapped into images of an inspected area that are smoothed in time. This data fusion method does not require any data association or multi-hypothesis tests that are usually prerequisite in localization of multiple targets. This yields a significantly lower computational complexity compared to other algorithms. We demonstrate the performance of our algorithm by an experimental measurement using 6 sensor nodes.","PeriodicalId":143107,"journal":{"name":"2011 IEEE International Conference on Ultra-Wideband (ICUWB)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":"{\"title\":\"Simple method for localisation of multiple tag-free targets using UWB sensor network\",\"authors\":\"R. Zetik, Snezhana Jovanoska, R. Thoma\",\"doi\":\"10.1109/ICUWB.2011.6058843\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article we propose a low complexity algorithm for detection and localization of multiple targets using UWB sensor networks. We assume that the targets being tracked do not have any devices or tags attached. They are localized using scattered electromagnetic waves. Our envisaged sensor network consists of sensor nodes that can autonomously detect and localize the closest target. Those partial location estimates are mapped into images of an inspected area that are smoothed in time. This data fusion method does not require any data association or multi-hypothesis tests that are usually prerequisite in localization of multiple targets. This yields a significantly lower computational complexity compared to other algorithms. We demonstrate the performance of our algorithm by an experimental measurement using 6 sensor nodes.\",\"PeriodicalId\":143107,\"journal\":{\"name\":\"2011 IEEE International Conference on Ultra-Wideband (ICUWB)\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"33\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Conference on Ultra-Wideband (ICUWB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICUWB.2011.6058843\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Ultra-Wideband (ICUWB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUWB.2011.6058843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simple method for localisation of multiple tag-free targets using UWB sensor network
In this article we propose a low complexity algorithm for detection and localization of multiple targets using UWB sensor networks. We assume that the targets being tracked do not have any devices or tags attached. They are localized using scattered electromagnetic waves. Our envisaged sensor network consists of sensor nodes that can autonomously detect and localize the closest target. Those partial location estimates are mapped into images of an inspected area that are smoothed in time. This data fusion method does not require any data association or multi-hypothesis tests that are usually prerequisite in localization of multiple targets. This yields a significantly lower computational complexity compared to other algorithms. We demonstrate the performance of our algorithm by an experimental measurement using 6 sensor nodes.