International Global Navigation Satellite Systems Association
IGNSS Conference 2016
Colombo Theatres, Kensington Campus, UNSW Australia
6 – 8 December 2016
A PPP-based Multi-sensor Fusion Positioning
Solution for Train Localization
Chengming Jin (1)
School of Electronic and Information Engineering/Beijing Jiaotong University/China
+61 0402706234 & chengming.jin@unimelb.edu.au
Allison Kealy (2)
Department of Infrastructure Engineering / The University of Melbourne /Australia
+61 0383446804 & a.kealy@unimelb.edu.au
Jian Wang (3)
School of Electronic and Information Engineering/Beijing Jiaotong University/China
+86 13810877610 & wangj@bjtu.edu.cn
Baigen Cai (4)
School of Electronic and Information Engineering/Beijing Jiaotong University/China
+86 01051687111 & bgcai@bjtu.edu.cn
ABSTRACT
GNSS-based train positioning is one of the most promising solutions for next
generation train control systems, e.g. the European Train Control System
(ETCS), Chinese Train Control System (CTCS). The key for implementing
GNSS-based positioning solution in railways application are the critical
RAMS (Reliability, Availability, Maintainability, and Safety) requirements.
This paper proposes a real-time Precise Point Positioning (PPP)-based multi-
sensor positioning system, which has property of high availability and
safety. Depending on different train operation scenarios, the proposed
fusion positioning and integrity check solution are intended to improve the
RAMS requirements. The integrity will be always monitored, so that critical
RAMS requirements are met seamlessly. The feasible system architectures
including real time PPP data transmission and GNSS/Odometer/INS fusion
positioning are presented in details.
The results of the developed solution indicate that GNSS/Odometer/INS
fusion results in better accuracy (0.76 m, 95%) in comparison with stand-
alone INS navigation (15.3 m, 95%). In spite of the fact that Kalman Filter
convergence process has an adverse impact on
detection, identification
and adaptation (DIA) quality control, this paper reveals DIA
procedure could be used as an integrity monitoring solution of Kalman
Filter-based multi-sensor fusion positioning.
KEYWORDS: Real-time PPP, Multi-sensor Fusion Positioning, Integrity
Monitoring, Train Localization
