惯性组合线形测量误差仿真与精度评估方法

doi:10.11947/j.AGCS.2026.20250428

测绘学报 ›› 2026, Vol. 55 ›› Issue (6): 1087-1100.doi: 10.11947/j.AGCS.2026.20250428

• 大型工程基础设施测绘与地下空间智能感知 • 上一篇

惯性组合线形测量误差仿真与精度评估方法

陈智鹏¹^,²^,³^,⁴(), 吕世望⁵, 王新一¹^,²^,³^,⁴()

^1.深圳大学城市空间信息工程系，广东　深圳　518060
^2.广东省城市空间信息工程重点实验室，广东　深圳　518060
^3.自然资源部大湾区地理环境监测重点实验室，广东　深圳　518060
^4.深圳市空间信息智能感知与服务重点实验室，广东　深圳　518060
^5.中铁第四勘察设计院集团有限公司，湖北　武汉　430063

收稿日期:2025-10-11 修回日期:2026-05-21 发布日期:2026-07-28
通讯作者: 王新一 E-mail:chenzp1990@szu.edu.cn;854756740@qq.com
作者简介:陈智鹏（1990—），男，博士，副教授，研究方向为组合定位、动态精密工程测量。E-mail：chenzp1990@szu.edu.cn
基金资助:
广东省基础与应用基础研究基金(2025A1515010216);国家重点研发计划(2025YFF1702803);中国铁道科学研究院集团有限公司研发计划(2024YJ397)

Error simulation and accuracy evaluation method for integrated inertial alignment measurement

Zhipeng CHEN¹^,²^,³^,⁴(), Shiwang LÜ⁵, Xinyi WANG¹^,²^,³^,⁴()

^1.Department of Urban Informatics, Shenzhen University, Shenzhen 518060, China
^2.Guangdong Key Laboratory of Urban Informatics, Shenzhen 518060, China
^3.Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Ministry of Natural Resources, Shenzhen 518060, China
^4.Shenzhen Key Laboratory of Spatial Information Intelligent Sensing and Services, Shenzhen 518060, China
^5.China Railway Siyuan Survey and Design Group Co., Ltd., Wuhan 430063, China

Received:2025-10-11 Revised:2026-05-21 Published:2026-07-28
Contact: Xinyi WANG E-mail:chenzp1990@szu.edu.cn;854756740@qq.com
About author:CHEN Zhipeng (1990—), male, PhD, associate professor, majors in integrated positioning and dynamic precision engineering surveying. E-mail: chenzp1990@szu.edu.cn
Supported by:
Guangdong Basic and Applied Basic Research Foundation(2025A1515010216);The National Key Research and Development Program of China(2025YFF1702803);Development Plan of China Academy of Railway Sciences Group Co., Ltd.(2024YJ397)

摘要/Abstract

摘要：

轨道、管道、桥梁等长距离线性工程的线形精密测量是运维安全的重要保障。近年来，惯性组合线形测量兼具高效、高精度的优势，在线形变化监测中逐渐广泛应用。但该测量方式的误差具有强非线性、多源耦合、时空累积特征，传统解析法难以精准量化分析。针对该工程痛点，本文提出了一种基于蒙特卡洛的误差仿真与精度评估方法：首先，采用样条函数拟合结合惯性编排反算实现轨迹高保真生成；其次，构建多源误差耦合模型并通过蒙特卡洛方法注入真实传感器误差；然后，利用卡尔曼滤波结合RTS平滑完成轨迹重构；最后，借助误差椭圆实现线形测量误差的可视化评估。分别对大坝内部预埋管道、铁路轨道等直线、U形线性结构测量开展仿真，结合大坝管道实测数据验证，仿真与实测数据平均相关性达87.3%。试验进一步分析了传感器精度、运动速度及控制点间距等因素对测量精度的影响规律。本文构建了“轨迹生成—误差注入—轨迹重构—精度评估”一体化方法体系，可有效支撑传感器选型、控制点布设等工程方案优化，为长距离线性工程变形监测提供技术参考。

关键词: 惯性里程计组合测量, 仿真模拟, 线形测量, 精度可视化

Abstract:

Precise alignment monitoring for long-distance linear infrastructure such as railway tracks, pipelines and bridges serves as a critical safeguard for operation and maintenance safety. In recent years, integrated inertial alignment measurement has been increasingly widely adopted in alignment variation monitoring, benefiting from its dual advantages of high efficiency and high precision. Nevertheless, the errors inherent in this measurement method feature strong nonlinearity, multi-source coupling and spatiotemporal accumulation, rendering traditional analytical methods incapable of accurate quantitative analysis. To tackle this practical engineering challenge, this paper proposes a Monte Carlo-based method for error simulation and accuracy evaluation. Specifically, high-fidelity trajectory generation is realized through spline function fitting combined with inverse calculation of inertial mechanization; a multi-source error coupling model is established, and realistic sensor errors are injected via the Monte Carlo approach; trajectory reconstruction is performed using Kalman filtering integrated with Rauch-Tung-Striebel (RTS) smoothing; and visualized assessment of alignment measurement errors is achieved by means of error ellipses. Simulations are carried out for measurement tasks on straight and U-shaped alignment structures, represented by pre-embedded pipelines inside dams and railway tracks. Validated with field measurement data from dam pipelines, the correlation coefficient between simulation results and measured data reaches 87.3%. Further experiments investigate the influence patterns of key factors including sensor accuracy, moving velocity and control point spacing on measurement accuracy. This study develops an integrated methodological framework covering trajectory generation, error injection, trajectory reconstruction and accuracy evaluation. It can effectively support the optimization of engineering schemes such as sensor selection and control point deployment, and provides technical reference for deformation monitoring of long-distance linear engineering structures.

Key words: integrated inertial-odometer measurement, simulation, alignment measurement, accuracy visualization

中图分类号:

P258

陈智鹏, 吕世望, 王新一. 惯性组合线形测量误差仿真与精度评估方法[J]. 测绘学报, 2026, 55(6): 1087-1100.

Zhipeng CHEN, Shiwang LÜ, Xinyi WANG. Error simulation and accuracy evaluation method for integrated inertial alignment measurement[J]. Acta Geodaetica et Cartographica Sinica, 2026, 55(6): 1087-1100.

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链接本文: http://xb.chinasmp.com/CN/10.11947/j.AGCS.2026.20250428

http://xb.chinasmp.com/CN/Y2026/V55/I6/1087

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坐标系符号	坐标系符号
地心惯性坐标系	i系
载体坐标系	b系
当地水平导航坐标系	n系

统计值	东坐标	北坐标	高程
最大值	12.64	13.22	2.93
最小值	－13.23	－11.17	－1.52
平均值	－0.04	－0.15	0.01

方法	东坐标RMSE/mm	北坐标RMSE/mm	高程RMSE/mm	相对精度
本文方法	3.21	3.57	0.89	0.23×10^－6
方法1	28.65	31.24	5.72	2.17×10^－6
方法2	15.32	16.87	3.24	1.12×10^－6

对比维度	本文方法	方法1	方法2
复杂形状线性工程仿真	是	否	是（但精度低）
多源误差耦合建模	是	否	是（但线性近似）
误差空间分布可视化	是	否	否
测量方案优化	是	否	有限

线形	管长/m	有效椭圆数	轴	平均轴长/m	最大轴长/m
直线形	300	15	长轴	0.004 0	0.004 8
直线形	300	15	短轴	0.003 1	0.003 5
U形	300	15	长轴	0.004 2	0.005 3
U形	300	15	短轴	0.003 5	0.004 3

惯性组合线形测量误差仿真与精度评估方法

Error simulation and accuracy evaluation method for integrated inertial alignment measurement

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参考文献 38

相关文章 15

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Metrics

本文评价

方向	实测线形重复性/mm	仿真线形重复性/mm	实测-仿真相关性/（%）
东方向	34.58	29.81	86.2
北方向	12.22	10.24	83.9
高程方向	4.16	3.82	91.8

精度分级	IMU（型号）	里程计速度中误差/（m/s）	控制点坐标中误差/m
高精度	导航级（kz50）	0.005	[0.001　0.001　0.001]
中精度	战术级（stim300 10g）	0.05	[0.01　0.01　0.01]
低精度	工业级（i300BA50）	0.5	[0.3　0.3　0.05]

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