# Real-time tightly coupled GNSS and IMU integration via Factor Graph Optimization

arXiv: https://arxiv.org/abs/2603.03556 · HTML: https://mlsanity.com/paper/2603.03556/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 17 references that are in the map.
- First posted on arXiv 3 Mar 2026.

## Builds on (most cited first, 4 of 4)

- [Towards Robust GNSS Positioning and Real-time Kinematic Using Factor Graph Optimization](https://mlsanity.com/paper/2106.01594/) (2021)
- [It is time for Factor Graph Optimization for GNSS/INS Integration: Comparison between FGO and EKF](https://mlsanity.com/paper/2004.10572/) (2020)
- [Open-Source Factor Graph Optimization Package for GNSS: Examples and Applications](https://mlsanity.com/paper/2502.08158/) (2025)
- [Adaptive Factor Graph-Based Tightly Coupled GNSS/IMU Fusion for Robust Positionin](https://mlsanity.com/paper/2511.23017/) (2025)

## Abstract (arXiv)

Reliable positioning in dense urban environments remains challenging due to frequent GNSS signal blockage, multipath, and rapidly varying satellite geometry. While factor graph optimization (FGO)-based GNSS-IMU fusion has demonstrated strong robustness and accuracy, most formulations remain offline. In this work, we present a real-time tightly coupled GNSS-IMU FGO method that enables causal state estimation via incremental optimization with fixed-lag marginalization, and we evaluate its performance in a highly urbanized GNSS-degraded environment using the UrbanNav dataset.