CredibleDFGO: Differentiable Factor Graph Optimization with Credibility Supervision
Global navigation satellite system (GNSS) positioning is widely used for urban navigation, but the covariance reported by the GNSS solver is often unreliable in urban canyons. Existing differentiable factor graph optimization (DFGO) methods learn measurement weighting through the solver, but they still use position-only objectives. As a result, the position estimate may improve while the reported covariance remains too small, too large, or incorrectly oriented. We propose CredibleDFGO (CDFGO), a differentiable GNSS factor graph framework that makes covariance credibility an explicit training target. A Weighting Generation Network (WGN) predicts per-satellite reliability weights, and a dif...
| Authors | Liang Qian, Penggao Yan, Penghui Xu et al. |
|---|---|
| Primary category | eess.SP |
| Published | 7 May 2026 |
| Last updated at source | 10 June 2026 |
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