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3D Mapping Database Aided GNSS RTK and Its Assessments in Urban Canyons

H.F., N., Hsu, L.T.

IEEE Transactions on Aerospace and Electronic Systems (2021)

journal Q1 Featured page
DOI
Urban test locations and sky masks used to assess 3D mapping database-aided GNSS RTK.
Figure 3 visual detail: Hong Kong test locations and sky masks used to evaluate 3D mapping database-aided GNSS RTK.

Summary

3D building models are used inside RTK processing to predict and exclude NLOS satellites before they corrupt ambiguity resolution.

Figures

After the pipeline defines 3D-map-aided RTK, this heatmap shows how candidate positions are scored before ambiguity resolution.

Heatmaps of position hypothesis mean square error and candidate score.
Figure 2: scoring position hypotheses with carrier-phase consistency.

The paper then tests the method across Hong Kong sites with different skyline obstruction patterns, making skymasks central to the evaluation.

Hong Kong experiment locations and skymasks at five urban test locations.
Figure 3: experiment locations and skymasks used for urban canyon assessment.

The shared antenna and receiver setup lets the study compare geodetic and commercial receivers under the same satellite environment.

Experiment equipment with antenna, splitter, geodetic receiver, commercial receiver, and PC.
Figure 4: experiment equipment for ground truth and RTK evaluation.

With the experiment fixed, the paper links positioning error to ambiguity dilution, geometry dilution, and satellite availability over time.

Positioning error, ADOP, PDOP, and satellite number time series for 3DMA GNSS RTK.
Figure 5: time-series comparison of positioning error, ambiguity dilution, geometry dilution, and satellite count.

The time-series behavior is summarized statistically to show how often the 3DMA-aided RTK solution improves the 2D error distribution.

CDF of 2D positioning error and box plots for 3DMA BIE RTK experiments.
Figures 6 and 7: distribution and box-plot summaries of 2D positioning error.

This diagnostic case explains the scoring behavior by comparing the position heatmap and visibility decisions at candidate locations.

Position heatmap and skymasks showing satellite selection at ground truth and 3DMA hypothesis.
Figure 8: position heatmap and skymask comparison explaining a noisy-measurement case.

The long-duration test checks whether the same visibility-based logic remains stable over several hours of urban data.

2D positioning error and visibility classification correctness over a three-hour experiment.
Figure 10: three-hour positioning error and visibility-classification correctness.

Key idea. Carrier-phase RTK collapses in urban canyons because reflected (NLOS) signals corrupt ambiguity resolution. This work brings a 3D building model into the RTK engine to predict and exclude NLOS satellites before they poison the solution.

Impact. It demonstrated that map-aware RTK can hold centimetre-class fixes in environments where conventional RTK fails — a building block of the lab’s 3D-mapping-aided GNSS line and its smartphone/automotive applications.

Related project and resources

Project: 3D Map-Aided GNSS (3DMA) for Smartphone and IoT