Show-Ling Jang, Byoungman An, Sanghun Yoon, Ki-Taeg Lim
{"title":"Research on the Indoor Environment Positioning Algorithm Using Sensor Fusion","authors":"Show-Ling Jang, Byoungman An, Sanghun Yoon, Ki-Taeg Lim","doi":"10.1109/ICEIC57457.2023.10049976","DOIUrl":null,"url":null,"abstract":"This paper proposes the indoor environment positioning algorithm using sensor fusion. The suggested method derived the positioning model for IMU (Inertial Measurement Unit) sensors and UWB (Ultra-wideband) sensors and combined them with EKF (Extended Kalman Filter). To verify the performance of the algorithm, the composite sensor module was constructed. The experiment was performed in an indoor environment. It was confirmed that the fusion of the two sensors is enough to satisfy the driving safety in the indoor environment. Consequently, the proposed algorithm showed that the closest positioning performance to a real trajectory comparing to the positioning performance with a conventional methodology of single sensor.","PeriodicalId":373752,"journal":{"name":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Electronics, Information, and Communication (ICEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEIC57457.2023.10049976","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
This paper proposes the indoor environment positioning algorithm using sensor fusion. The suggested method derived the positioning model for IMU (Inertial Measurement Unit) sensors and UWB (Ultra-wideband) sensors and combined them with EKF (Extended Kalman Filter). To verify the performance of the algorithm, the composite sensor module was constructed. The experiment was performed in an indoor environment. It was confirmed that the fusion of the two sensors is enough to satisfy the driving safety in the indoor environment. Consequently, the proposed algorithm showed that the closest positioning performance to a real trajectory comparing to the positioning performance with a conventional methodology of single sensor.