Summary of Positioning Error in the North Direction on Test Data Sets
Our algorithm outperforms all of the baselines on the test data sets with respect to mean, median and minimum metric and provides a comparable maximum positioning error. Note that the median, minimum, and maximum errors in the north direction were unavailable for the attention-based neural network baseline.
| Error Metric (m) | Kalman Filter | Attention (Kanhere et al., 2022) | Loose GNN + Kalman Filter (Mohanty & Gao, 2022) | Our Approach |
|---|---|---|---|---|
| Mean | 3.0 | 6.4 | 2.0 | 1.9 |
| Median | 2.1 | - | 1.8 | 1.8 |
| Minimum | 1.3 | - | 1.0 | 0.7 |
| Maximum | 7.7 | - | 5.7 | 5.8 |