{"title":"Fingerprinting-based wireless 3D localization for motion capture applications","authors":"M. Giuberti, M. Martalò, G. Ferrari","doi":"10.1145/2007036.2007044","DOIUrl":null,"url":null,"abstract":"In this paper, we consider a radio fingerprinting-based localization system for indoor motion capture applications. Fingerprinting allows target localization on the basis of radio-frequency measurements of the Received radio Signal Strength (RSS), taking into account the presence of fading by means of a training phase. Motion capture is then performed by localizing, through fingerprinting, a group of targets placed on the portion of interest of the user arm---the approach can be easily extended to other portions of the user body. We experimentally investigate, through a SunSPOT wireless sensor network test-bed, different fingerprinting-based localization algorithms, namely deterministic and probabilistic, optimizing, in each case, the system parameters. In particular, the optimization is carried out by minimizing the localization error.","PeriodicalId":150900,"journal":{"name":"International Workshop on Pervasive Wireless Healthcare","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Pervasive Wireless Healthcare","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2007036.2007044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper, we consider a radio fingerprinting-based localization system for indoor motion capture applications. Fingerprinting allows target localization on the basis of radio-frequency measurements of the Received radio Signal Strength (RSS), taking into account the presence of fading by means of a training phase. Motion capture is then performed by localizing, through fingerprinting, a group of targets placed on the portion of interest of the user arm---the approach can be easily extended to other portions of the user body. We experimentally investigate, through a SunSPOT wireless sensor network test-bed, different fingerprinting-based localization algorithms, namely deterministic and probabilistic, optimizing, in each case, the system parameters. In particular, the optimization is carried out by minimizing the localization error.