An Integrated Navigation Approach Utilizing Factor Graph Optimization

For the GNSS/INS integrated navigation, the traditional filtering algorithm is difficult to take into account the historical state information and time correlation of satellite observations. To this end, this paper proposes a tightly coupled GNSS/INS positioning algorithm based on factor graphs. In this method, the pseudorange, solved preliminary satellite positions and the pre-integration information of the IMU are added as factor nodes. Introduce the position and attitude information of the UAV and the position information of the satellites as variable nodes to realize the factor graph optimization of the solution model. In this paper, static GNSS data and IMU data are collected, and the factor graph method and the traditional integrated navigation algorithm are experimentally verified and compared under the data. The results show that the method proposed in this paper can improve the positioning accuracy by more than 40% compared with the traditional method in the urban satellite-constrained environment.