期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
基于高斯过程回归的Wi-Fi RTT/RSS测距与指纹定位研究
1
作者 谢思语 王鑫龙 +5 位作者 邱燕华 李彤云 师嘉怡 汪云甲 陈国良 孙猛 《导航定位与授时》 CSCD 2024年第5期36-52,共17页
基于往返时间(RTT)测量的智能手机Wi-Fi测距定位受限于室内环境的复杂性,仍面临稳定性差、精度低等问题。利用同步量测的Wi-Fi RTT和信号接收强度(RSS)数据,分别从测距与指纹补偿、测距定位与匹配定位优化等方面开展研究。首先,通过分析... 基于往返时间(RTT)测量的智能手机Wi-Fi测距定位受限于室内环境的复杂性,仍面临稳定性差、精度低等问题。利用同步量测的Wi-Fi RTT和信号接收强度(RSS)数据,分别从测距与指纹补偿、测距定位与匹配定位优化等方面开展研究。首先,通过分析RTT测距误差规律,建立了基于高斯过程回归(GPR)的非参数测距误差补偿模型;研究了RSS数据分布,通过拟合Wi-Fi信号路径衰减模型,构建了基于GPR的RSS补偿模型。其次,开发了基于Web端的指纹库生成和指纹定位软件,可支持RSS指纹库、RTT测距指纹库自主建设和RSS/RTT指纹定位。最后,设计了基于GPR补偿的RTT测距定位、RTT指纹定位和Wi-Fi RSS指纹匹配定位算法,并综合分析了3种方法的定位性能。实验结果表明,经过高斯补偿的RTT测距定位、RTT指纹定位和RSS指纹定位的平均精度分别提升了50.81%、52.85%和48.72%,证明了高斯过程回归模型可有效提升Wi-Fi RTT/RSS测距与指纹定位的精度与稳定性。 展开更多
关键词 室内定位 高斯过程回归 wi-fi精细时间测量 往返时间 指纹定位 测距定位
下载PDF
Indoor positioning based on tightly coupling of PDR and one single Wi-Fi FTM AP 被引量:3
2
作者 Yuan Wu Ruizhi Chen +3 位作者 Wenju Fu Wei Li Haitao Zhou Guangyi Guo 《Geo-Spatial Information Science》 SCIE EI CSCD 2023年第3期480-495,共16页
The indoor positioning system is now an important technique as part of the Internet-of-Things(IoT)ecosystem.Among indoor positioning techniques,multiple Wi-Fi Access Points(APs)-based positioning systems have been res... The indoor positioning system is now an important technique as part of the Internet-of-Things(IoT)ecosystem.Among indoor positioning techniques,multiple Wi-Fi Access Points(APs)-based positioning systems have been researched a lot.There is a lack of research focusing on the scene where only one Wi-Fi AP is available.This work proposes a hybrid indoor positioning system that takes advantage of the Fine-Timing Measurements(FTM)technique that is part of the IEEE 802.11mc standard,introduced back in 2016.The system uses one single Wi-Fi FTM AP and takes advantage of the built-in inertial sensors of the smartphone to estimate the device’s position.We explore both Loosely Coupled(LC)and Tightly Coupled(TC)integration schemes for the sensors’data fusion.Experimental results show that the proposed methods can achieve an average positioning accuracy of about 1 m without knowing the initial position.Compared with the LC integration method,the median error accuracy of the proposed TC fusion algorithm has improved by more than 52%and 67%,respectively,in the two experiments we set up. 展开更多
关键词 Indoor positioning wi-fi fine Time measurement(ftm)/Round Trip Time(RTT) Tightly Coupled(TC)integration Pedestrian Dead Reckoning(PDR) Extended Kalman Filter(EKF)
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部