基于蓝牙低功耗的数字按键定位方法研究

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}
引用次数: 0

摘要

蓝牙技术和移动通信技术的发展,使得智能手机取代传统的车钥匙成为可能。为了在车载环境中实现智能手机的高精度定位和准确识别,本文采用了基于蓝牙低功耗(BLE)技术的位置指纹方法。在离线指纹数据库构建阶段,采用基于移动平均和卡尔曼滤波的融合滤波算法,获得更稳定的数据。在定位识别阶段,提出了一种基于位置坐标相似性的二元k均值聚类结合加权k近邻(WKNN)算法对智能手机进行定位识别。实验结果表明,与k近邻(KNN)算法相比,该算法将智能手机的识别精度提高了8.8%,并将定位误差从1.56m降低到0.41m。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信