基于几何辅助ble的智能手机室内定位服务

2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM) Pub Date : 2020-11-23 DOI:10.1109/ICMIM48759.2020.9299009

Branislav Rudić, Maria Anneliese Klaffenböck, Markus Pichler-Scheder, D. Efrosinin, C. Kastl

{"title":"基于几何辅助ble的智能手机室内定位服务","authors":"Branislav Rudić, Maria Anneliese Klaffenböck, Markus Pichler-Scheder, D. Efrosinin, C. Kastl","doi":"10.1109/ICMIM48759.2020.9299009","DOIUrl":null,"url":null,"abstract":"Self-positioning of smartphones in indoor environments offers a wide variety of applications. Anyway, in harsh environments, the achievable accuracies using received signal strength indicator measurement data are comparably low. However, restrictions due to geometry allow more accurate estimates of smartphone positions and trajectories. Based on received signal strength data from Bluetooth low energy beacons and Gaussian assumptions, an application of a discrete-state hidden Markov model – taking the geometry into account – in combination with dynamic model parameter estimation, leads to a significant improvement of error statistics.","PeriodicalId":150515,"journal":{"name":"2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Geometry-Aided BLE-Based Smartphone Positioning for Indoor Location-Based Services\",\"authors\":\"Branislav Rudić, Maria Anneliese Klaffenböck, Markus Pichler-Scheder, D. Efrosinin, C. Kastl\",\"doi\":\"10.1109/ICMIM48759.2020.9299009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Self-positioning of smartphones in indoor environments offers a wide variety of applications. Anyway, in harsh environments, the achievable accuracies using received signal strength indicator measurement data are comparably low. However, restrictions due to geometry allow more accurate estimates of smartphone positions and trajectories. Based on received signal strength data from Bluetooth low energy beacons and Gaussian assumptions, an application of a discrete-state hidden Markov model – taking the geometry into account – in combination with dynamic model parameter estimation, leads to a significant improvement of error statistics.\",\"PeriodicalId\":150515,\"journal\":{\"name\":\"2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMIM48759.2020.9299009\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMIM48759.2020.9299009","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

智能手机在室内环境中的自我定位提供了各种各样的应用。无论如何，在恶劣的环境下，使用接收到的信号强度指标测量数据所能达到的精度是比较低的。然而，由于几何形状的限制，可以更准确地估计智能手机的位置和轨迹。基于蓝牙低能信标接收到的信号强度数据和高斯假设，将考虑几何形状的离散状态隐马尔可夫模型与动态模型参数估计相结合，显著改善了误差统计。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Geometry-Aided BLE-Based Smartphone Positioning for Indoor Location-Based Services

Self-positioning of smartphones in indoor environments offers a wide variety of applications. Anyway, in harsh environments, the achievable accuracies using received signal strength indicator measurement data are comparably low. However, restrictions due to geometry allow more accurate estimates of smartphone positions and trajectories. Based on received signal strength data from Bluetooth low energy beacons and Gaussian assumptions, an application of a discrete-state hidden Markov model – taking the geometry into account – in combination with dynamic model parameter estimation, leads to a significant improvement of error statistics.

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

2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)

自引率

0.00%

发文量