测绘通报 ›› 2024, Vol. 0 ›› Issue (11): 78-82.doi: 10.13474/j.cnki.11-2246.2024.1114

• 工程测量分会年会优选论文 • 上一篇    

附加UWB约束的GNSS/INS组合导航算法

周涛1, 邹进贵1, 赵胤植1, 周振南1, 伍靖雯1, 黄俊峰2, 闵会2   

  1. 1. 武汉大学测绘学院, 湖北 武汉 430079;
    2. 湖北省自然资源厅测绘应急保障中心, 湖北 武汉 430064
  • 收稿日期:2024-07-24 发布日期:2024-12-05
  • 作者简介:周涛(1995-),男,博士生,主要研究方向为多源融合组合导航。E-mail:taozhou_whu@163.com
  • 基金资助:
    国家自然科学基金(41871373);湖北省自然科学基金计划(2024AFB166)

GNSS/INS integrated navigation algorithm with UWB constraints

ZHOU Tao1, ZOU Jingui1, ZHAO Yinzhi1, ZHOU Zhennan1, WU Jingwen1, HUANG Junfeng2, MIN Hui2   

  1. 1. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;
    2. Surveying and Mapping Emergency Support Center, Department of Natural Resources of Hubei Province, Wuhan 430064, China
  • Received:2024-07-24 Published:2024-12-05

摘要: 针对传统组合导航算法在卫星信号拒止和室内环境下难以适用的问题,本文使用超宽带(UWB)定位技术辅助GNSS/INS导航系统,推导了附加UWB约束的组合导航卡尔曼滤波模型,在数据处理层面,利用UWB距离测量的先验方差构建噪声矩阵;为验证其有效性,在武汉大学防空洞进行了推车试验。结果表明,UWB定位信息的加入能够有效抑制速度和位置的快速发散,在GNSS信号中断50 s后,E、N、U 3个方向的速度漂移分别为0.236、0.284和0.179 m/s,位置漂移为5.247 m,导航精度相较于传统算法,提高了80%以上。

关键词: 组合导航, 低成本, 超宽带, 卡尔曼滤波

Abstract: In order to solve the problem of traditional integrated navigation algorithms being difficult to apply in satellite signal rejection and indoor environments,ultra wideband (UWB) positioning technology is considered to assist GNSS/INS navigation systems. We derive a combined navigation Kalman filter model with additional UWB constraints and construct a noise matrix using the prior variance of UWB distance measurement at the data processing level. To verify the effectiveness of the proposed method, we conduct a trolley experiment in the air raid shelter of Wuhan university. The experimental results show that the addition of UWB positioning information can effectively suppress the rapid divergence of velocity and position. After 50 seconds of GNSS signal interruption, the velocity drift in the E, N, and U directions is 0.236, 0.284, and 0.179 m/s,respectively, and the position drift is 5.247 m. The navigation positioning accuracy is improved by more than 80% compared to traditional algorithms.

Key words: integrated navigation, low cost, ultra wideband, Kalman filtering

中图分类号: