Factor Graph Fusion Localization Method with Tight and Loose Coupling of GNSS/IMU and Odometry

Objectives We investigate the impact of information fusion at different depths on the accuracy of navigation systems composed of micro inertial navigation systems (M-INS) and global navigation satellite systems (GNSS), as well as indoor and outdoor integrated positioning.

Methods First, based on the factor graph optimization (FGO) algorithm, a loosely coupled system of M-INS/single-point GNSS and a tightly coupled system of M-INS/pseudorange/Doppler velocity are established respectively, and the advantages of the tightly coupled design are verified by experiments. Then, the visual inertial odometry (VIO) factor is inserted into the factor structure of the tightly coupled M-INS/GNSS system in a loosely coupled manner, and a tight- loosely coupled multi-source fusion algorithm model based on FGO is proposed. Finally, the positioning accuracy and indoor and outdoor integrated positioning capability of the system are verified by experiments.

Results The experimental results show that:(1) When four satellites cannot be observed and the single-point positioning solution cannot be obtained, the positioning accuracy of the M-INS/GNSS tightly coupled system can reach twice that of the M-INS/GNSS loosely coupled system. (2) In the case of the sudden failure of either GNSS or VIO, the FGO-based M-INS/GNSS/VIO tight-loosely coupled system can continue to provide reliable positioning, and the average errors of the east and north directions are improved by 53.98% and 54.74% respectively compared with the M-INS/GNSS/VIO system based on the filtering method.

Conclusions Compared with the loosely coupled M-INS/GNSS system, the M-INS/GNSS tightly coupled system effectively reduces the impact of GNSS signal instability on the system, and has higher accuracy and robustness. The proposed tightly-loosely coupled system can seamlessly respond to changes between indoor and outdoor environments.