测绘通报 ›› 2026, Vol. 0 ›› Issue (3): 75-79.doi: 10.13474/j.cnki.11-2246.2026.0313

• 学术研究 • 上一篇    下一篇

铁路综合测量系统平台的高精度航迹线位姿解算

李民, 周乐韬   

  1. 西南交通大学地球科学与环境工程学院, 四川 成都 611756
  • 收稿日期:2025-08-27 发布日期:2026-04-08
  • 通讯作者: 周乐韬。E-mail:ltzhou@swjtu.edu.cn
  • 作者简介:李民(2000—),男,硕士,研究方向为多源融合导航定位。E-mail:2455275267@qq.com
  • 基金资助:
    国家重点研发计划(2022YFC3005703)

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

LI Min, ZHOU Letao   

  1. School of Earth Science Engineering, Southwest Jiaotong University, Chengdu 611756, China
  • Received:2025-08-27 Published:2026-04-08

摘要: 针对铁路工务智能精确检修的运营需求,本文构建了基于GNSS+IMU+里程计组合定位定姿技术的多源异构数据融合框架,提出了一种在卫星数量受限(少于4颗)情况下引入里程计联合优化的OJTC算法,旨在解决卫星观测受限场景下位姿精度的提升与长时间失锁后模糊度加速固定问题。试验结果表明,OJTC算法在位置、速度及姿态估计精度上显著优于传统方法,且长时间失锁后模糊度平均固定时间缩短至9 s,相较RTK、松组合(LC)和紧组合(TC)分别提升了57.1%、47.1%、35.7%,实现了铁路综合测量系统平台的高精度航迹线解算。该高精度航迹线为轨道几何状态智能诊断与精准维修提供了可靠的数据基础。

关键词: GNSS, 惯性导航系统, 里程计, 多源融合, 模糊度固定

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

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