Refined On-Manifold IMU Preintegration Theory for Factor Graph Optimization Based on Equivalent Rotation Vector

Multi-source information fusion is a major area of interest within the field of unmanned technology. In comparison with utilizing the Kalman Filter (KF) based method, the factor graph optimization (FGO)-based method has recently been proposed as an innovative approach. However, the traditional FGO-b...

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Bibliographic Details
Published in:IEEE sensors journal 2023-03, Vol.23 (5), p.1-1
Main Authors: Ding, Jicheng, Huang, Chenglin, Cheng, Jianhua, Wang, Feng, Hu, Yanan
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Data integration
Equivalence
equivalent rotation vector
factor graph optimization
Global navigation satellite system
Heuristic algorithms
Inertial navigation
Inertial platforms
Inertial sensing devices
Kalman filters
Manifolds
multi-sample algorithm
Navigation systems
on-manifold IMU preintegration
Optimization
Rotation
Rotation measurement
Smoothing methods
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Summary:Multi-source information fusion is a major area of interest within the field of unmanned technology. In comparison with utilizing the Kalman Filter (KF) based method, the factor graph optimization (FGO)-based method has recently been proposed as an innovative approach. However, the traditional FGO-based inertial measurement unit (IMU) preintegration process is designed for low-accuracy inertial sensors, which leads to insufficient utilization of information and decrease the positioning accuracy, in the case of tactical-grade or higher accuracy IMUs. Therefore, this paper refines the process on the manifold model and utilizes the equivalent rotation vector to accumulate IMU measurements. The main contribution of our work is the refined on-manifold IMU preintegration theory and the application of the multi-sample algorithm based on the equivalent rotation vector for obtaining more precise preintegrated IMU measurements. The refined on-manifold IMU preintegration theory is applied based on the FGO algorithm in the global navigation satellite system (GNSS) / inertial navigation system (INS) loosely integrated navigation system. The experiments based on simulated and real-world data were conducted and demonstrate that, compared to a high-precision EKF algorithm and optimization methods, the proposed method achieves more accuracy in a dynamic environment.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2023.3233966