{"title":"在基本RSS位置管理技术中增加到达角度模态","authors":"E. Elnahrawy, John Austen-Francisco, R. Martin","doi":"10.1109/ISWPC.2007.342648","DOIUrl":null,"url":null,"abstract":"In this paper, we describe a radio-based localization approach that is based on the use of rotating directional antennas and a Bayesian network that combines both angle-of-arrival (AoA) and received signal strength (RSS). After describing our network, we extensively characterize the accuracy of our approach under a variety of measured signal distortion types. Next, using a combination of synthetic and trace-driven experiments, we show the impact of different signal distortions on localization performance. We found the use of directional antennas was effective at averaging out multi-path effects in indoor environments, which helped reduce the amount of training data required compared to previous approaches.","PeriodicalId":403213,"journal":{"name":"2007 2nd International Symposium on Wireless Pervasive Computing","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"53","resultStr":"{\"title\":\"Adding Angle of Arrival Modality to Basic RSS Location Management Techniques\",\"authors\":\"E. Elnahrawy, John Austen-Francisco, R. Martin\",\"doi\":\"10.1109/ISWPC.2007.342648\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we describe a radio-based localization approach that is based on the use of rotating directional antennas and a Bayesian network that combines both angle-of-arrival (AoA) and received signal strength (RSS). After describing our network, we extensively characterize the accuracy of our approach under a variety of measured signal distortion types. Next, using a combination of synthetic and trace-driven experiments, we show the impact of different signal distortions on localization performance. We found the use of directional antennas was effective at averaging out multi-path effects in indoor environments, which helped reduce the amount of training data required compared to previous approaches.\",\"PeriodicalId\":403213,\"journal\":{\"name\":\"2007 2nd International Symposium on Wireless Pervasive Computing\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"53\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 2nd International Symposium on Wireless Pervasive Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISWPC.2007.342648\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 2nd International Symposium on Wireless Pervasive Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISWPC.2007.342648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adding Angle of Arrival Modality to Basic RSS Location Management Techniques
In this paper, we describe a radio-based localization approach that is based on the use of rotating directional antennas and a Bayesian network that combines both angle-of-arrival (AoA) and received signal strength (RSS). After describing our network, we extensively characterize the accuracy of our approach under a variety of measured signal distortion types. Next, using a combination of synthetic and trace-driven experiments, we show the impact of different signal distortions on localization performance. We found the use of directional antennas was effective at averaging out multi-path effects in indoor environments, which helped reduce the amount of training data required compared to previous approaches.