Technical gazette, Vol. 30 No. 1, 2023.
Original scientific paper
https://doi.org/10.17559/TV-20221019035741
UWB-INS Fusion Positioning Based on a Two-Stage Optimization Algorithm
Yiran Liu
; China Academy of Railway Sciences Corporation Limited, 2 Daliushu Road, Haidian District, Beijing, China
Yushan Zhang
; China Academy of Railway Sciences Corporation Limited, 2 Daliushu Road, Haidian District, Beijing, China
Yan Jiang
; China Railway Beijing Group Corporation Limited, 6 Fuxing Road, Haidian District, Beijing, China
Weiping Liu
; China Academy of Railway Sciences Corporation Limited, 2 Daliushu Road, Haidian District, Beijing, China
Fenghao Yang
orcid.org/0000-0001-8186-6364
; Beijing University of Posts and Telecommunications, 10 Xitucheng Road, Haidian District, Beijing, China
Abstract
Ultra-wideband (UWB) is a carrier-less communication technology that transmits data using narrow pulses of non-sine waves on the nanosecond scale. The UWB positioning system uses the multi-lateral positioning algorithm to accurately locate the target, and the positioning accuracy is seriously affected by the non-line-of-sight (NLOS) error. The existing non-line-of-sight error compensation methods lack multidimensional consideration. To combine the advantages of various methods, a two-stage UWB-INS fusion localization algorithm is proposed. In the first stage, an NLOS signal filter is designed based on support vector machines (SVM). In the second stage, the results of UWB and Inertial Navigation System (INS) are fused based on Kalman filter algorithm. The two-stage fusion localization algorithm achieves a great improvement on positioning system, it can improve the localization accuracy by 79.8% in the NLOS environment and by 36% in the (line-of-sight) LOS environment.
Keywords
inertial navigation system; Kalman filter; machine learning; optimal estimation; UWB
Hrčak ID:
288411
URI
Publication date:
15.12.2022.
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