# Seamless Outdoor-Indoor Pedestrian Positioning System with GNSS/UWB/IMU Fusion: A Comparison of EKF, FGO, and PF

arXiv: https://arxiv.org/abs/2512.10480 · HTML: https://mlsanity.com/paper/2512.10480/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Dec 2025.

## Built on by (most cited first, 2 of 2)

- [Urban Risk-Aware Navigation via VQA-Based Event Maps for People with Low Vision](https://mlsanity.com/paper/2605.11782/) (2026)
- [Spotter: Efficient Urban Visual Localization via Geo-Referenced Facade Landmarks in GPS-Degraded Environments](https://mlsanity.com/paper/2608.23290/) (2026)

## Abstract (arXiv)

Accurate and continuous pedestrian positioning across outdoor-indoor environments remains challenging because GNSS, UWB, and inertial PDR are complementary yet individually fragile under signal blockage, multipath, and drift. This paper presents a unified GNSS/UWB/IMU fusion framework for seamless pedestrian localization and provides a controlled comparison of three probabilistic back-ends: an error-state extended Kalman filter, sliding-window factor graph optimization, and a particle filter. The system uses chest-mounted IMU-based PDR as the motion backbone and integrates absolute updates from GNSS outdoors and UWB indoors. To enhance transition robustness and mitigate urban GNSS degradation, we introduce a lightweight map-based feasibility constraint derived from OpenStreetMap building footprints, treating most building interiors as non-navigable while allowing motion inside a designated UWB-instrumented building. The framework is implemented in ROS 2 and runs in real time on a wearable platform, with visualization in Foxglove. We evaluate three scenarios: indoor (UWB+PDR), outdoor (GNSS+PDR), and seamless outdoor-indoor (GNSS+UWB+PDR). Results show that the ESKF provides the most consistent overall performance in our implementation.