因子图框架下里程计辅助GNSS/INS组合导航算法

doi:10.13474/j.cnki.11-2246.2024.0311

测绘通报 ›› 2024, Vol. 0 ›› Issue (3): 63-68.doi: 10.13474/j.cnki.11-2246.2024.0311

因子图框架下里程计辅助GNSS/INS组合导航算法

唐卫明¹, 戚克培¹, 邓辰龙², 邹璇¹, 李洋洋¹, 胡泽奇³

1. 武汉大学卫星导航定位技术研究中心, 湖北武汉 430079;
2. 武汉理工大学航运学院, 湖北武汉 430063;
3. 湖北文理学院汽车与交通工程学院, 湖北襄阳 441053

收稿日期:2023-08-07 发布日期:2024-04-08
作者简介:唐卫明(1978—),男,博士,教授,主要从事GNSS实时动态定位应用开发和系统集成研究工作。E-mail:wmtang@whu.edu.cn
基金资助:
国家重点研发计划(2022YFB3904602)

An odometer-aided GNSS/INS integrated navigation algorithm under the framework of FGO

TANG Weiming¹, QI Kepei¹, DENG Chenlong², ZOU Xuan¹, LI Yangyang¹, HU Zeqi³

1. GNSS Research Center, Wuhan University, Wuhan 430079, China;
2. School of Navigation, Wuhan University of Technology, Wuhan 430063, China;
3. School of Automotive and Traffic Engineering, Hubei University of Arts and Science, Xiangyang 441053, China

Received:2023-08-07 Published:2024-04-08

摘要/Abstract

摘要： 在复杂观测环境下,GNSS/INS组合导航系统的GNSS信号易受干扰从而导致INS独立导航精度迅速下降。针对上述问题,本文基于因子图的里程计辅助GNSS/INS组合导航算法,利用里程计观测信息结合非完整性约束构建航向速度约束方程,同时采用能多次线性化计算和多次迭代的因子图优化方法进行参数估计。实际车载试验解算结果表明,在GNSS信号良好时,基于因子图方法比滤波方法具有更快的收敛时间,收敛速度提高了近10倍;在GNSS信号发生中断时,添加里程计辅助后组合导航系统在东向和北向分别提升了83%和89%。与传统的滤波融合手段相比,本文采用因子图优化后在东向和北向的定位精度分别有63%、70%的改善。

关键词: GNSS, INS, 轮式里程计, 因子图优化, 组合导航

Abstract: In a complex observation environment, the GNSS signal of the GNSS/INS integrated navigation system is susceptible to be disturbed and result in a rapid decline in the accuracy of INS independent navigation. Aiming at the above problems, this paper studies the odometer-assisted GNSS/INS integrated navigation algorithm based on the factor graph, uses the odometer observation information combined with the non-holonomic constraint to construct the heading speed constraint equation, and adopts factor graph optimization for parameter estimation which conducts multiple linearization calculations and multiple iterations at the same time. The results of real vehicle experiments show that when the GNSS signal is good, the factor graph-based method has a faster convergence time than the filtering method, and the convergence speed is increased by about 10 times; when the GNSS signal is interrupted, the positioning accuracy of odometer-assisted integrated navigation system in the E and U direction has increased by 83% and 89% respectively. And compared with the conventional Kalman filter method, the positioning accuracy in the E and N can respectively be improved by using factor graph optimization in this paper. There are 63% and 70% improvements.

Key words: GNSS, INS, wheel odometer, factor graph optimization, integrated navigation

中图分类号:

P228

唐卫明, 戚克培, 邓辰龙, 邹璇, 李洋洋, 胡泽奇. 因子图框架下里程计辅助GNSS/INS组合导航算法[J]. 测绘通报, 2024, 0(3): 63-68.

TANG Weiming, QI Kepei, DENG Chenlong, ZOU Xuan, LI Yangyang, HU Zeqi. An odometer-aided GNSS/INS integrated navigation algorithm under the framework of FGO[J]. Bulletin of Surveying and Mapping, 2024, 0(3): 63-68.

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因子图框架下里程计辅助GNSS/INS组合导航算法

An odometer-aided GNSS/INS integrated navigation algorithm under the framework of FGO

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