This paper presents a robust train localisation system by fusing a Global Navigation Satellite System (GNSS) with an Inertial Navigation System (INS) in a tightly-coupled (TC) strategy. To improve navigation performance in GNSS partly blocked areas, an advanced map-matching (MM) measurement-augmented TC GNSS/INS method is proposed via an error-state unscented Kalman filter (UKF). The advanced MM generates a matched position using a one-step predicted position from a UKF time update step with binary search algorithm and a point-line projection algorithm. The matched position inputs as an additional measurement to fuse with the INS position to augment the degraded GNSS pseudorange measurement to optimise the state estimation in the UKF measurement update step. Both the real train test on the Qinghai-Tibet railway and the simulation were carried out and the results confirm that the proposed advanced MM measurement-augmented TC GNSS/INS with error-state UKF provides the best horizontal positioning accuracy of 0 center dot 67 m, which performs an improvement of about 71% and 90% with respect to TC GNSS/INS with only error-state UKF and only error-state Extended Kalman filter in GNSS partly blocked areas.
机构:
School of Electronic and Information Engineering, Beijing Jiaotong University, BeijingSchool of Electronic and Information Engineering, Beijing Jiaotong University, Beijing
Liu D.
Jiang W.
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机构:
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing
Beijing Engineering Technology Research Center, BeijingSchool of Electronic and Information Engineering, Beijing Jiaotong University, Beijing
Jiang W.
Cai B.
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机构:
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing
Beijing Engineering Technology Research Center, BeijingSchool of Electronic and Information Engineering, Beijing Jiaotong University, Beijing
Cai B.
Wang J.
论文数: 0引用数: 0
h-index: 0
机构:
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing
Beijing Engineering Technology Research Center, BeijingSchool of Electronic and Information Engineering, Beijing Jiaotong University, Beijing
Wang J.
Shangguan W.
论文数: 0引用数: 0
h-index: 0
机构:
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing
Beijing Engineering Technology Research Center, BeijingSchool of Electronic and Information Engineering, Beijing Jiaotong University, Beijing
Shangguan W.
Tiedao Xuebao/Journal of the China Railway Society,
2023,
45
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: 62
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71