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Robustly Adaptive EKF PDR/UWB Integrated Navigation Based on Additional Heading Constraint.

Authors :
Yuan, Debao
Zhang, Jian
Wang, Jian
Cui, Ximin
Liu, Fei
Zhang, Yalei
Source :
Sensors (14248220); Jul2021, Vol. 21 Issue 13, p4390-4390, 1p
Publication Year :
2021

Abstract

At present, GNSS (Global Navigation Satellite System) positioning technology is widely used for outdoor positioning services because of its high-precision positioning characteristics. However, in indoor environments, effective position information cannot be provided, because of the signals being obscured. In order to improve the accuracy and continuity of indoor positioning systems, in this paper, we propose a PDR/UWB (Pedestrian Dead Reckoning and Ultra Wide Band) integrated navigation algorithm based on an adaptively robust EKF (Extended Kalman Filter) to address the problem of error accumulation in the PDR algorithm and gross errors in the location results of the UWB in non-line-of-sight scenarios. First, the basic principles of UWB and PDR location algorithms are given. Then, we propose a loose combination of the PDR and UWB algorithms by using the adaptively robust EKF. By using the robust factor to adjust the weight of the observation value to resist the influence of the gross error, and by adjusting the variance of the system adaptively according to the positioning scene, the algorithm can improve the robustness and heading factor of the PDR algorithm, which is constrained by indoor maps. Finally, the effectiveness of the algorithm is verified by the measured data. The experimental results showed that the algorithm can not only reduce the accumulation of PDR errors, but can also resist the influence of gross location errors under non-line-of-sight UWB scenarios. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14248220
Volume :
21
Issue :
13
Database :
Complementary Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
151314953
Full Text :
https://doi.org/10.3390/s21134390