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CSI Fingerprinting Localization With Low Human Efforts
IEEE/ACM Transactions on Networking ( IF 3.0 ) Pub Date : 2020-11-16 , DOI: 10.1109/tnet.2020.3035210
Xinyu Tong 1 , Yang Wan 2 , Qianru Li 2 , Xiaohua Tian 2 , Xinbing Wang 2
Affiliation  

Fingerprinting indoor localization systems exploit wireless signal propagation features to estimate the location of wireless devices, where the major challenge in practice is the all-consuming training process: it requires site survey to establish the mapping between the signal feature and the location where the feature is observed. In this paper, we present a Wi-Fi localization scheme based on channel state information (CSI) of wireless signals, which manages to relieve time-consuming site survey. In particular, we first propose how to automatically generate the theoretical fingerprints database based on the signal propagation model and geometric methods. Localization with the theoretical fingerprints database yields accuracy close to existing methods. Second, we improve localization accuracy by parsing the user’s trajectory instead of restricting to the single spot, where human movement features introduce more information for localization. Third, we present an automatic update scheme for the theoretical fingerprints database to improve time efficiency for localization, which can save 94 – 98% processing time for utilizing the CSI fingerprints database. We implement a prototype with COTS devices and conduct comprehensive experiments to verify proposed mechanisms. Results show that our design achieves 80% localization errors within $0.3m$ , which is $3\times $ accuracy compared with the state-of-the-art design leveraging CSI.

中文翻译:

无需人工的CSI指纹本地化

室内室内指纹系统利用无线信号传播功能来估计无线设备的位置,而实践中的主要挑战是全过程的培训过程:需要现场调查以建立信号功能与功能所在位置之间的映射观测到的。在本文中,我们提出了一种基于无线信号的信道状态信息(CSI)的Wi-Fi本地化方案,该方案可减轻费时的站点调查。特别是,我们首先提出如何基于信号传播模型和几何方法自动生成理论指纹数据库。使用理论指纹数据库进行本地化可产生接近现有方法的准确性。第二,我们通过解析用户的轨迹而不是限制在单个位置上来提高定位精度,在该位置上人类的移动功能会引入更多的定位信息。第三,我们为理论指纹数据库提出了一种自动更新方案,以提高本地化的时间效率,这可以节省使用CSI指纹数据库的94 – 98%的处理时间。我们使用COTS设备实现了原型,并进行了全面的实验以验证提出的机制。结果表明,我们的设计在80%内实现了本地化错误 使用CSI指纹数据库可以节省94 – 98%的处理时间。我们使用COTS设备实现了原型,并进行了全面的实验以验证提出的机制。结果表明,我们的设计在80%的定位误差内 使用CSI指纹数据库可以节省94 – 98%的处理时间。我们使用COTS设备实现了原型,并进行了全面的实验以验证提出的机制。结果表明,我们的设计在80%的定位误差内 30万美元 ,这是 $ 3 \次$ 与使用CSI的最新设计相比,其准确性更高。
更新日期:2020-11-16
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