Research on Extended Kalman Filter and Particle Filter Combinational Algorithm in UWB and Foot-Mounted IMU Fusion Positioning
Joint Authors
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-07-03
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Telecommunications Engineering
Abstract EN
As UWB high-precision positioning in NLOS environment has become one of the hot topics in the research of indoor positioning, this paper firstly presents a method for the smoothing of original range data based on the Kalman filter by the analysis of the range error caused by UWB signals in LOS and NLOS environment.
Then, it studies a UWB and foot-mounted IMU fusion positioning method with the integration of particle filter with extended Kalman filter.
This method adopts EKF algorithm in the kinematic equation of particle filters algorithm to calculate the position of each particle, which is like the way of running N (number of particles) extended Kalman filters, and overcomes the disadvantages of the inconformity between kinematic equation and observation equation as well as the problem of sample degeneration under the nonlinear condition of the standard particle filters algorithm.
The comparison with the foot-mounted IMU positioning algorithm, the optimization-based UWB positioning algorithm, the particle filter-based UWB positioning algorithm, and the particle filter-based IMU/UWB fusion positioning algorithm shows that our algorithm works very well in LOS and NLOS environment.
Especially in an NLOS environment, our algorithm can better use the foot-mounted IMU positioning trajectory maintained by every particle to weaken the influence of range error caused by signal blockage.
It outperforms the other four algorithms described as above in terms of the average and maximum positioning error.
American Psychological Association (APA)
Li, Xin& Wang, Yan& Liu, Dawei. 2018. Research on Extended Kalman Filter and Particle Filter Combinational Algorithm in UWB and Foot-Mounted IMU Fusion Positioning. Mobile Information Systems،Vol. 2018, no. 2018, pp.1-17.
https://search.emarefa.net/detail/BIM-1204668
Modern Language Association (MLA)
Li, Xin…[et al.]. Research on Extended Kalman Filter and Particle Filter Combinational Algorithm in UWB and Foot-Mounted IMU Fusion Positioning. Mobile Information Systems No. 2018 (2018), pp.1-17.
https://search.emarefa.net/detail/BIM-1204668
American Medical Association (AMA)
Li, Xin& Wang, Yan& Liu, Dawei. Research on Extended Kalman Filter and Particle Filter Combinational Algorithm in UWB and Foot-Mounted IMU Fusion Positioning. Mobile Information Systems. 2018. Vol. 2018, no. 2018, pp.1-17.
https://search.emarefa.net/detail/BIM-1204668
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1204668