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. 2024 Apr 24;24(9):2712.
doi: 10.3390/s24092712.

Modified RTK-GNSS for Challenging Environments

Ellarizza Fredeluces  1 , Tomohiro Ozeki  1 , Nobuaki Kubo  1 , Ahmed El-Mowafy  2
Affiliations

Modified RTK-GNSS for Challenging Environments

Ellarizza Fredeluces et al. Sensors (Basel). .

Abstract

Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS) is currently the premier technique for achieving centimeter-level accuracy quickly and easily. However, the robustness of RTK-GNSS diminishes in challenging environments due to severe multipath effects and a limited number of available GNSS signals. This is a pressing issue, especially for GNSS users in the navigation industry. This paper proposes and evaluates several methodologies designed to overcome these issues by enhancing the availability and reliability of RTK-GNSS solutions in urban environments. Our novel approach involves the integration of conventional methods with a new technique that leverages surplus satellites-those not initially used for positioning-to more reliably detect incorrect fix solutions. We conducted three tests in densely built-up areas within the Tokyo region. The results demonstrate that our approach not only surpasses the fix rate of the latest commercial receivers and a popular open-source RTK-GNSS program but also improves positional reliability to levels comparable to or exceeding those of the aforementioned commercial technology.

Keywords: RTK; multipath; navigation; reliability.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 16
Figure 16
Horizontal plot of u-blox F9P showing large errors (encircled region).
Figure 17
Figure 17
Horizontal plot of Modified RTK-GNSS showing large errors (encircled region).
Figure 1
Figure 1
Implemented relative positioning method.
Figure 2
Figure 2
Outlier detection method.
Figure 3
Figure 3
Concept of ambiguity resolution using velocity information.
Figure 4
Figure 4
General flow of validating the ambiguity solution after passing the ratio test.
Figure 5
Figure 5
Rover and base antenna on the rooftop for static test.
Figure 6
Figure 6
RTK position results of antenna located on rooftop.
Figure 7
Figure 7
Summary of 95th percentile error of ambiguity difference for every double-difference pair.
Figure 8
Figure 8
Validating recalculated DD ambiguity.
Figure 9
Figure 9
Experimental test courses. (a) First test course in Marunouchi and Ginza areas. (b) Second test course in Toranomon and Shimbashi areas. (c) Third test course in Odaiba area.
Figure 10
Figure 10
Setup of car experiment.
Figure 11
Figure 11
Setup of base station.
Figure 12
Figure 12
Ground track and horizontal time-series error plot of float solutions of first test course.
Figure 13
Figure 13
Groundtrack and horizontal time-series error plot of float solutions of second test course.
Figure 14
Figure 14
Groundtrack and horizontal time-series error plot of float solutions of third test course.
Figure 15
Figure 15
Fix rate comparison of Modified RTK-GNSS and u-blox F9P.
Figure 18
Figure 18
2DRMS comparison of three RTK-GNSS engines using the same parameters.
Figure 19
Figure 19
2DRMS comparison of three RTK-GNSS engines using different parameters.
See this image and copyright information in PMC

References

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