基于蓝牙定位信息的井下RSSI校正与定位改进算法研究

Yadi Wu, Senlin Cheng, Xiaohao Yan
{"title":"基于蓝牙定位信息的井下RSSI校正与定位改进算法研究","authors":"Yadi Wu, Senlin Cheng, Xiaohao Yan","doi":"10.1145/3424978.3425131","DOIUrl":null,"url":null,"abstract":"In order to overcome positioning accuracy being lower of Bluetooth caused by the uncertainty and other interference factors under the mine well environment, the paper proposed an improved RSSI correction location algorithm based on Bluetooth positioning information. The algorithm firstly carried on the data pre-filtering based on secondary filter to reduce the gross error and interference of RSSI sampled data, secondly built a piecewise path loss model based on sliding window by means of logarithmic path loss model to fit the relationship between distance and RSSI better, and finally integrated Bluetooth positioning information into the improved fine weight three-circle positioning to estimate the unknown node location accurately. Taking the corridor-type mine well environment as an example, the experimental data verified that the method could effectively reduce the ranging error, and the highest positioning accuracy could reach to 0.11 meter, and compared with the general weighted triangular centroid positioning method, its average error could reduce about 27%. The study results show that the proposed improvement method in this paper is reasonable and feasible.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"234 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Study on Improved Algorithm of RSSI Correction and Location in Mine-well Based on Bluetooth Positioning Information\",\"authors\":\"Yadi Wu, Senlin Cheng, Xiaohao Yan\",\"doi\":\"10.1145/3424978.3425131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to overcome positioning accuracy being lower of Bluetooth caused by the uncertainty and other interference factors under the mine well environment, the paper proposed an improved RSSI correction location algorithm based on Bluetooth positioning information. The algorithm firstly carried on the data pre-filtering based on secondary filter to reduce the gross error and interference of RSSI sampled data, secondly built a piecewise path loss model based on sliding window by means of logarithmic path loss model to fit the relationship between distance and RSSI better, and finally integrated Bluetooth positioning information into the improved fine weight three-circle positioning to estimate the unknown node location accurately. Taking the corridor-type mine well environment as an example, the experimental data verified that the method could effectively reduce the ranging error, and the highest positioning accuracy could reach to 0.11 meter, and compared with the general weighted triangular centroid positioning method, its average error could reduce about 27%. The study results show that the proposed improvement method in this paper is reasonable and feasible.\",\"PeriodicalId\":178822,\"journal\":{\"name\":\"Proceedings of the 4th International Conference on Computer Science and Application Engineering\",\"volume\":\"234 5\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 4th International Conference on Computer Science and Application Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3424978.3425131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3424978.3425131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

针对矿井环境下蓝牙定位精度不确定等干扰因素导致定位精度较低的问题,本文提出了一种基于蓝牙定位信息的改进RSSI校正定位算法。该算法首先进行基于二次滤波的数据预滤波,降低RSSI采样数据的粗误差和干扰,其次利用对数路径损失模型构建基于滑动窗口的分段路径损失模型,更好地拟合距离与RSSI之间的关系,最后将蓝牙定位信息集成到改进的细权三圆定位中,准确估计未知节点位置。以巷道式矿井环境为例,实验数据验证了该方法能有效减小测距误差,最高定位精度可达0.11 m,与一般加权三角质心定位方法相比,其平均误差可减小27%左右。研究结果表明,本文提出的改进方法是合理可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Study on Improved Algorithm of RSSI Correction and Location in Mine-well Based on Bluetooth Positioning Information
In order to overcome positioning accuracy being lower of Bluetooth caused by the uncertainty and other interference factors under the mine well environment, the paper proposed an improved RSSI correction location algorithm based on Bluetooth positioning information. The algorithm firstly carried on the data pre-filtering based on secondary filter to reduce the gross error and interference of RSSI sampled data, secondly built a piecewise path loss model based on sliding window by means of logarithmic path loss model to fit the relationship between distance and RSSI better, and finally integrated Bluetooth positioning information into the improved fine weight three-circle positioning to estimate the unknown node location accurately. Taking the corridor-type mine well environment as an example, the experimental data verified that the method could effectively reduce the ranging error, and the highest positioning accuracy could reach to 0.11 meter, and compared with the general weighted triangular centroid positioning method, its average error could reduce about 27%. The study results show that the proposed improvement method in this paper is reasonable and feasible.
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
期刊最新文献
Study on Improved Algorithm of RSSI Correction and Location in Mine-well Based on Bluetooth Positioning Information Distributed Predefined-time Consensus Tracking Protocol for Multi-agent Systems Evaluation Method Study of Blog's Subject Influence and User's Subject Influence Performance Evaluation of Full Turnover-based Policy in the Flow-rack AS/RS A Hybrid Encoding Based Particle Swarm Optimizer for Feature Selection and Classification
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1