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Enhanced INS/GNSS State Estimation using GNSS-Based Acceleration Measurements
Gal Versano, · 2026-05-26 · via cs updates on arXiv.org

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Abstract:Accurate and reliable navigation is essential for autonomous ground vehicle operations. Standard INS/GNSS fusion relies on GNSS position updates, which provide limited observability of orientation and inertial sensor error states, particularly during low-dynamic motion. In this work, we propose utilizing past GNSS measurements alongside a motion model to extract meaningful vehicle acceleration information. This acceleration measurement is then integrated into the INS/GNSS filter to improve its robustness and accuracy. The proposed approach is evaluated on two real-world unmanned ground vehicle datasets collected from different mobile platforms and inertial sensor grades. Results demonstrate consistent positioning accuracy improvements relative to the standard position-aided filter, with mean position root mean square error improvements of 11.40 % and 20.74 % on the two datasets, respectively.
Subjects: Robotics (cs.RO)
Cite as: arXiv:2605.24767 [cs.RO]
  (or arXiv:2605.24767v1 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2605.24767

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Gal Versano [view email]
[v1] Sat, 23 May 2026 23:04:30 UTC (1,064 KB)