Publications
Detailed Information
Indoor localization by kalman filter based combining of UWB-positioning and PDR
Cited 15 time in
Web of Science
Cited 20 time in Scopus
- Authors
- Issue Date
- 2021-01
- Citation
- 2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021
- Abstract
- © 2021 IEEE.Ultra-wideband (UWB) ranging-based indoor positioning system (IPS) is suggested as one of the solutions to satisfy the requirement of decimeter level accuracy in indoor environments. However, UWB ranging error caused in non-line-of-sight (NLOS) environments is inevitable, which reduces accuracy of positioning. To tackle this problem, in this paper, an indoor positioning scheme that combines UWB positioning with pedestrian dead reckoning (PDR) is designed and proposed. First, the proposed scheme improves the performance of PDR utilizing UWB positioning in order to achieve the effect of parameter adaptation used in PDR. To this end, step detection and stride length estimation in traditional PDR are substituted with a deep learning-based speed estimation. In addition, heading estimation is improved by calibrating tilt effect of smartphone with the aid of UWB positioning. Then, with the UWB-assisted PDR (U-PDR), we also propose UWB positioning and U-PDR fusion algorithm using Kalman filter (KF). The proposed fusion algorithm complements UWB positioning and U-PDR based positioning, which improves the accuracy of positioning. Experimental results demonstrates that the performance of the proposed algorithm is better than that of UWB positioning or PDR only algorithms.
- Files in This Item:
- There are no files associated with this item.
Item View & Download Count
Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.