Version 1
: Received: 27 May 2024 / Approved: 27 May 2024 / Online: 27 May 2024 (08:31:03 CEST)
How to cite:
Qiu, H.; Zhao, Y.; Wang, H.; Wang, L. A Study on Graph Optimization Method for GNSS/IMU Integrated Navigation System Based on Virtual Constraints. Preprints2024, 2024051697. https://doi.org/10.20944/preprints202405.1697.v1
Qiu, H.; Zhao, Y.; Wang, H.; Wang, L. A Study on Graph Optimization Method for GNSS/IMU Integrated Navigation System Based on Virtual Constraints. Preprints 2024, 2024051697. https://doi.org/10.20944/preprints202405.1697.v1
Qiu, H.; Zhao, Y.; Wang, H.; Wang, L. A Study on Graph Optimization Method for GNSS/IMU Integrated Navigation System Based on Virtual Constraints. Preprints2024, 2024051697. https://doi.org/10.20944/preprints202405.1697.v1
APA Style
Qiu, H., Zhao, Y., Wang, H., & Wang, L. (2024). A Study on Graph Optimization Method for GNSS/IMU Integrated Navigation System Based on Virtual Constraints. Preprints. https://doi.org/10.20944/preprints202405.1697.v1
Chicago/Turabian Style
Qiu, H., Hui Wang and Lei Wang. 2024 "A Study on Graph Optimization Method for GNSS/IMU Integrated Navigation System Based on Virtual Constraints" Preprints. https://doi.org/10.20944/preprints202405.1697.v1
Abstract
In GNSS/IMU integrated navigation systems, factors such as satellite occlusion and non-line-of-sight conditions can lead to degradation of satellite positioning results, Subsequently affecting the overall accuracy of the integrated navigation system. To address this issue and ef-fectively utilize historical pseudorange information from satellites, this paper proposes a graph optimization-based GNSS/IMU model with virtual constraints. These virtual constraints are con-structed using satellite ‘s position from previous time step, the rate of change of pseudoranges, and ephemeris data. This virtual constraint can serve as an alternative solution for individual satellites in case of signal anomalies, ensuring the integrity and continuity of the graph optimi-zation model. Additionally, this paper conducts an analysis of the graph optimization model constructed using these virtual constraints, comparing it with traditional integrated navigation graph optimization model, and analyzes and reconstructs the marginalization process based on these virtual constraints. The experimental results, compared with tightly coupled Kalman fil-tering and the original graph optimization method on a set of real-world data, demonstrate that the introduction of virtual pseudoranges maintains high positioning accuracy. The RMSE error between it and the original graph optimization remains within 5%, affirming the high feasibility of this approach.
Keywords
graph optimization; GNSS/IMU integrated navigation; Kalman Filter; SLAM
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
