{"title":"Step-Detection Algorithm for Indoor Localization System Using Mobile Phone Sensors","authors":"Szabina Zékány","doi":"10.26649/musci.2019.035","DOIUrl":null,"url":null,"abstract":"Many of the indoor localization algorithms rely on predictor-corrector methods. In the prediction phase the algorithm estimates the user’s position in the next timeframe and the correction phase uses some kind of location specific measurement to refine the position. For indoor navigation systems developed for human users the most obvious prediction method is determining the heading of user using the built-in compass of the mobile phone and detecting and analyzing the walking motion step-by-step. Knowing the actual position of the person and combining the step and heading information the next estimated position can be determined. The step detection is based on the acquired data from a mobile phone sensor filtered and processed by an appropriate algorithm in order to determine the user motion state. The paper presents the development and results of such an algorithm.","PeriodicalId":340250,"journal":{"name":"MultiScience - XXXIII. microCAD International Multidisciplinary Scientific Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MultiScience - XXXIII. microCAD International Multidisciplinary Scientific Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26649/musci.2019.035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Many of the indoor localization algorithms rely on predictor-corrector methods. In the prediction phase the algorithm estimates the user’s position in the next timeframe and the correction phase uses some kind of location specific measurement to refine the position. For indoor navigation systems developed for human users the most obvious prediction method is determining the heading of user using the built-in compass of the mobile phone and detecting and analyzing the walking motion step-by-step. Knowing the actual position of the person and combining the step and heading information the next estimated position can be determined. The step detection is based on the acquired data from a mobile phone sensor filtered and processed by an appropriate algorithm in order to determine the user motion state. The paper presents the development and results of such an algorithm.