Comparative Evaluation of GNSS Positioning Accuracy Using RTK Techniques and CORS-Based Post-Processing Solutions
Bibliographic record
Abstract
Global Navigation Satellite System (GNSS) applications in Osun State, Nigeria, are limited by poor positional accuracy, particularly in vertical measurements. With the recent establishment of a Continuously Operating Reference Station (CORS) by private surveyors, it is important to assess the performance of real-time and post-processed GNSS solutions for local survey practice. This study compared two real-time kinematic (RTK) connection methods: radio frequency (RF) and network RTK via internet (NRTK) with static precise positioning using Canadian Spatial Reference System Precise Point Positioning (CSRS-PPP) and Osun CORS RINEX data processed in South Geomatics Office software. Field data were collected on three control stations with a Tersus Oscar GNSS receiver, and accuracy was evaluated using root mean square error (RMSE) against published control coordinates. Results show that CSRS-PPP (0.11 m easting, 0.17 m northing, 3.78 m height) and Osun CORS (0.09 m easting, 0.11 m northing, 3.76 m height) achieved horizontal accuracies within the allowable 0.05-0.50 m limit, but vertical errors exceeded the 0.10 m tolerance. NRTK (0.06 m easting, 0.03 m northing) performed better than RF-RTK (0.53 m easting, 1.29 m northing) for horizontal positioning, yet both produced unacceptable vertical errors of 24.14 m and 8.54 m, respectively. The findings confirm that online PPP and internet-based RTK provide reliable horizontal accuracy in Osun State, but vertical accuracy remains inadequate and requires further methodological improvement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".