GNSS/INS/Visual Integrated Navigation Algorithm and Performance Analysis Based on Factor Graph Optimization

Regarding the issue of rapid divergence of navigation errors in GNSS/INS integrated navigation systems during GNSS signal interruptions, this paper proposes a GNSS/INS/visual integrated navigation algorithm based on factor graph optimization to improve positioning performance when GNSS signals are disrupted. By constructing a factor graph framework for GNSS/INS/visual integrated navigation, the performance of three navigation schemes—RTK (G), RTK/INS (GI), and RTK/INS/visual (GIV)—was tested and analyzed in a complex urban environment. Experimental results demonstrate that the introduction of visual information significantly suppresses the divergence of the combined navigation algorithm's positioning results during GNSS interruptions. Compared to the GI scheme, the GIV scheme improves positioning accuracy by 60.96% in the east direction, 42.19% in the north direction, and 59.39% in the vertical direction, thus validating the effectiveness of the proposed factor graph-based GNSS/INS/visual integrated navigation algorithm in enhancing overall navigation system performance.