Skoči na glavni sadržaj

Izvorni znanstveni članak

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 id orcid.org/0000-0001-8186-6364 ; Beijing University of Posts and Telecommunications, 10 Xitucheng Road, Haidian District, Beijing, China


Puni tekst: engleski pdf 1.399 Kb

str. 185-190

preuzimanja: 224

citiraj


Sažetak

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.

Ključne riječi

inertial navigation system; Kalman filter; machine learning; optimal estimation; UWB

Hrčak ID:

288411

URI

https://hrcak.srce.hr/288411

Datum izdavanja:

15.12.2022.

Posjeta: 575 *