Yang Xu, Xingyu Yang, Jingtao Zhang, Jianjie Yang, Jie Tang
{"title":"基于蓝牙低功耗的数字按键定位方法研究","authors":"Yang Xu, Xingyu Yang, Jingtao Zhang, Jianjie Yang, Jie Tang","doi":"10.1109/CAC57257.2022.10055246","DOIUrl":null,"url":null,"abstract":"The development of Bluetooth technology and mobile communication technology makes it possible for smartphones to replace traditional car keys. In order to achieve high-precision positioning and accurate identification of smartphones in the vehicle environment, this paper adopts a location fingerprint method based on Bluetooth Low Energy (BLE) technology. In the stage of offline fingerprint database construction, a fusion filtering algorithm based on moving average and Kalman filtering is used to obtain more stable data. In the phase of location and identification, a binary K-means clustering based on the similarity of position coordinates combined with weighted K-nearest neighbor (WKNN) algorithm is proposed to locate and identify smartphones. The experimental results show that the proposed algorithm improves the recognition accuracy of smartphones by 8.8% compared with the K-nearest neighbor (KNN) algorithm, and reduces the positioning error from 1.56m to 0.41m.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Digital Key Positioning Method Based on Bluetooth Low Energy\",\"authors\":\"Yang Xu, Xingyu Yang, Jingtao Zhang, Jianjie Yang, Jie Tang\",\"doi\":\"10.1109/CAC57257.2022.10055246\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development of Bluetooth technology and mobile communication technology makes it possible for smartphones to replace traditional car keys. In order to achieve high-precision positioning and accurate identification of smartphones in the vehicle environment, this paper adopts a location fingerprint method based on Bluetooth Low Energy (BLE) technology. In the stage of offline fingerprint database construction, a fusion filtering algorithm based on moving average and Kalman filtering is used to obtain more stable data. In the phase of location and identification, a binary K-means clustering based on the similarity of position coordinates combined with weighted K-nearest neighbor (WKNN) algorithm is proposed to locate and identify smartphones. The experimental results show that the proposed algorithm improves the recognition accuracy of smartphones by 8.8% compared with the K-nearest neighbor (KNN) algorithm, and reduces the positioning error from 1.56m to 0.41m.\",\"PeriodicalId\":287137,\"journal\":{\"name\":\"2022 China Automation Congress (CAC)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 China Automation Congress (CAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAC57257.2022.10055246\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 China Automation Congress (CAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAC57257.2022.10055246","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Digital Key Positioning Method Based on Bluetooth Low Energy
The development of Bluetooth technology and mobile communication technology makes it possible for smartphones to replace traditional car keys. In order to achieve high-precision positioning and accurate identification of smartphones in the vehicle environment, this paper adopts a location fingerprint method based on Bluetooth Low Energy (BLE) technology. In the stage of offline fingerprint database construction, a fusion filtering algorithm based on moving average and Kalman filtering is used to obtain more stable data. In the phase of location and identification, a binary K-means clustering based on the similarity of position coordinates combined with weighted K-nearest neighbor (WKNN) algorithm is proposed to locate and identify smartphones. The experimental results show that the proposed algorithm improves the recognition accuracy of smartphones by 8.8% compared with the K-nearest neighbor (KNN) algorithm, and reduces the positioning error from 1.56m to 0.41m.