On-line smoothing and error modelling for integration of GNSS and visual odometry

Thanh Trung Duong, Kai Wei Chiang, Dinh Thuan Le

研究成果: Article

摘要

Global navigation satellite systems (GNSSs) are commonly used for navigation and mapping applications. However, in GNSS-hostile environments, where the GNSS signal is noisy or blocked, the navigation information provided by a GNSS is inaccurate or unavailable. To overcome these issues, this study proposed a real-time visual odometry (VO)/GNSS integrated navigation system. An on-line smoothing method based on the extended Kalman filter (EKF) and the Rauch-Tung-Striebel (RTS) smoother was proposed. VO error modelling was also proposed to estimate the VO error and compensate the incoming measurements. Field tests were performed in various GNSS-hostile environments, including under a tree canopy and an urban area. An analysis of the test results indicates that with the EKF used for data fusion, the root-mean-square error (RMSE) of the three-dimensional position is about 80 times lower than that of the VO-only solution. The on-line smoothing and error modelling made the results more accurate, allowing seamless on-line navigation information. The efficiency of the proposed methods in terms of cost and accuracy compared to the conventional inertial navigation system (INS)/GNSS integrated system was demonstrated.

原文English
文章編號5259
期刊Sensors (Switzerland)
19
發行號23
DOIs
出版狀態Published - 2019 十二月 1

指紋

satellite navigation systems
smoothing
Navigation
Aleurites
Satellites
navigation
Costs and Cost Analysis
Kalman filters
Extended Kalman filters
inertial navigation
canopies
root-mean-square errors
multisensor fusion
field tests
Signal systems
Inertial navigation systems
Data fusion
Navigation systems
costs
Mean square error

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

引用此文

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On-line smoothing and error modelling for integration of GNSS and visual odometry. / Duong, Thanh Trung; Chiang, Kai Wei; Le, Dinh Thuan.

於: Sensors (Switzerland), 卷 19, 編號 23, 5259, 01.12.2019.

研究成果: Article

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