High-precision trajectory and pose estimation for integrated railway measurement system platforms

doi:10.13474/j.cnki.11-2246.2026.0313

Abstract

Abstract: To meet the operational demands of intelligent and precise maintenance in railway infrastructure,this paper proposes a multi-source heterogeneous data fusion framework based on GNSS+IMU+odometer integrated positioning and orientation technology.A novel odometer joint tightly coupled (OJTC) algorithm is introduced to address the challenges of pose estimation accuracy under limited satellite visibility (fewer than four satellites) and to accelerate ambiguity resolution after long-term GNSS signal loss.Experimental results demonstrate that the OJTC algorithm significantly outperforms conventional methods in terms of position,velocity,and attitude estimation accuracy.Moreover,the average ambiguity fixing time after signal outage is reduced to 9 s,achieving improvements of 57.1%,47.1%,and 35.7%compared to RTK,loose couple(LC),and tight couple(TC) methods,respectively.The proposed framework enables high-precision trajectory computation for railway measurement platforms,providing a reliable spatial foundation for intelligent diagnosis and precise maintenance of track geometry.

Key words: GNSS, INS, odometer, multi-sensor fusion, ambiguity resolution

CLC Number:

P228

LI Min, ZHOU Letao. High-precision trajectory and pose estimation for integrated railway measurement system platforms[J]. Bulletin of Surveying and Mapping, 2026, 0(3): 75-79.

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