Article citation information:
Krasuski, K., Bakuła, M., Miduch, P. Accuracy
analysis of vehicle positioning using GPS and GLONASS data. Scientific Journal of Silesian University of
Technology. Series Transport. 2026, 132,
197-217. ISSN: 0209-3324. DOI: https://doi.org/10.20858/sjsutst.2026.132.11
Kamil KRASUSKI[1], Mieczysław BAKUŁA[2], Piotr MIDUCH[3]
ACCURACY ANALYSIS OF VEHICLE POSITIONING USING GPS AND GLONASS DATA
Summary. The article
presents a new computational strategy for determining the positioning accuracy
parameter in car navigation, based on a multi-receiver solution of the SPP code
method. The experiment was conducted in kinematic mode using five GNSS
receivers mounted on the roof of the vehicle. These receivers recorded code
observations from the GPS and GLONASS systems at a frequency of 1 Hz. For each
receiver, the position was determined separately using the SPP code method
based on GPS measurements, GLONASS measurements, and combined GPS/GLONASS
measurements. The calculated positions were compared with the reference
trajectory obtained using the PPP (Precise Point Positioning) technique. The
results of the experiment demonstrate the benefits of multi-system positioning.
The average RMS errors for geodetic coordinates (B, L, h) were: GPS – 0.21 m,
0.53 m, 2.06 m; GLONASS – 1.34 m, 1.83 m, 1.78 m; GPS/GLONASS – 0.34 m, 0.73 m,
1.51 m. These results indicate that the combined GPS/GLONASS solution reduces
the total positioning error compared to GLONASS alone. In addition, the
combined solution improves only the vertical component, but it worsens the
horizontal accuracy compared with GPS alone. The accuracies obtained (RMS in
the order of meters) are many times better than the 20 m limit
specified for road navigation systems, which proves the practical usefulness of
the developed method.
Keywords: accuracy,
car navigation, GPS, GLONASS, GNSS
1.
INTRODUCTION
GNSS
satellite systems are widely used in air, sea, and land navigation [1]. In land
navigation, an important application is car navigation [2], with particular
emphasis on determining the position, speed, and acceleration of a moving
object [3]. Initially, only the GPS navigation system was used to determine the
coordinates of a car's movement [4], but now all global GNSS systems are used
in car navigation [5]. The standard GNSS positioning model for car navigation
is based on the SPP code method [6]. The SPP code method is used in both static
and kinematic GNSS measurements to determine the coordinates of an object [7,
8]. The observation model of the SPP code method is based on the measurement of
at least 4 pseudoranges between the position of the
GNSS satellite and the position of the mobile receiver located in the car [9].
In addition to the observed pseudoranges, it is
necessary to know the position of the satellite at a given moment in time, the
time of transmission of the satellite signal from the satellite, and the time
of reception of the satellite signal by the receiver [10]. Furthermore, it is
crucial to properly model systematic errors occurring in code measurement, such
as: ephemeris error, satellite clock error, ionospheric and tropospheric
correction, hardware delay for the satellite, relativistic correction,
multipath effect, etc. [11]. The application of the SPP code method in car
navigation will be shown in the literature review in subsection 1.1.
1.1. Related
works
It
is worth starting the literature review with the requirements for GNSS
satellite systems in terms of their practical application in car navigation.
Based on [12], it can be concluded that the accuracy requirements for road
transport are as follows:
-
navigation and traffic control up to 20 m,
-
road accident alerts up to 30 m,
-
transport management up to 1500 m,
-
automatic notification of scheduled bus stops up to 30
m,
-
vehicle guidance and control up to 50 m,
-
collision avoidance for critical situations up to 5 m,
-
accident data collection up to 30 m,
-
infrastructure management up to 10 m,
-
collision avoidance for control up to 1 m.
The
study [12] shows that the accuracy of determining the position of a car cannot
exceed 20 m. The specified accuracy requirements are a reference for other
publications from the state of the art analysis, in which the SPP code method
was used to determine the position of a car. Thus, in [13], the results of the
positioning accuracy of a small agricultural vehicle used on coffee plantations
in Brazil are presented. During the research, the average positioning accuracy
was 1.42 m horizontally and 7.12 m vertically. Subsequently, in [14], the
results of simulations to determine the position of a car in an urban canyon
and in a heavily built-up area were presented. In particular, a model for
collecting and exchanging GNSS data from moving cars and an algorithm for
determining the multipath effect for GNSS measurements were presented. In the
worst-case scenario of a simulation in a heavily urbanized area, the accuracy
of car positioning, expressed by the RMS error, falls below 20 m. Another
publication [15] investigated the usefulness of GNSS receivers for monitoring
car collisions. The accuracy of coordinate determination measured by CEP error
was 2.5 m, although errors of the order of 10 m occurred during the 24-hour
session. This means that the SPP method may prove insufficient to improve
safety in traffic management. However, in [5], the possibility of using GNSS
observations to improve kinematic positioning in road transport, especially in
urban canyons. The tests achieved a positioning accuracy of better than 5 m.
The study utilized GNSS data, LIDAR data, a camera, and sound sensors. The next
publication [16] showed the possibility of using the SPP code method and other
GNSS positioning methods for automatic driving of cars with built-in sensors
and applications. The article highlights recommendations, solutions, and
technical considerations for the development of such an IT system for cars.
Publications [17, 18] present the concept of integrating GNSS data with SPP
solutions and the use of cameras or LIDAR sensors to improve kinematic
positioning in urban canyons among large buildings. The paper develops an
algorithm for detecting GNSS signals that do not reach the receiver located in
the car. The results of the research confirm the effectiveness of the developed
solution in highly urbanized areas such as Hong Kong. Similar research can be
seen in [19], which also integrates SPP GNSS and LIDAR data. In this case, the
accuracy of the object's trajectory reconstruction was 8.8 m with the SPP GNSS
+ LIDAR solution. In turn, article [20] presents the application of a deep
learning model for the prediction and correction of SPP GNSS positioning errors
in a highly urbanized environment. The study determined the availability of SPP
GNSS positioning, which was 100%. The paper [21] investigated the possibility
of using Android phones to determine the position of a car while driving.
During the research, the accuracy of horizontal coordinates was up to 30 m, and
the accuracy of altitude was up to 45 m. The study examined the impact of
measurement noise on GNSS code and phase observations. Another study [22]
showed the results of applying GNSS data filtering to improve positioning using
the SPP code method. The development of algorithms for detecting errors in GNSS
code measurements was particularly important. The developed method allows for
position determination in dynamic measurements with an accuracy of 8 m. Publication
[23] presented the combination of a GNSS sensor and IMU for the purpose of
improving dynamic positioning. In addition, a Kalman filter was used to
determine the coordinates of the car. The developed method allows for an
improvement in the determination of horizontal coordinates by almost 66-68%
within SPP positioning. Another paper [24] compared the positioning accuracy of
SPP and PPP methods for road navigation in the Philippines. In the case of the
SPP method, the accuracy was over 10 m, while with the PPP method it was less
than 1 m. Article [25] demonstrates the possibility of using BDS-3 generation
satellites for road transport. It also compares the positioning results of SPP
with those of the GPS navigation system. Paper [26] develops an improved RAIM
algorithm for the RANSAC model. The RANSAC model was tested for SPP positioning
in laboratory conditions and in a real dynamic experiment. Article [27]
examines the impact of SPP positioning accuracy on road safety. At low traffic
volumes, the impact of accuracy can be ignored. However, at high traffic
density, A-GNSS assistance systems need to be developed so that the accuracy of
kinematic positioning is higher.
The analysis
of the current state of knowledge leads to the following conclusions:
-
the issue of using GNSS satellite technology in car
navigation and road transport in general is quite important,
-
GNSS positioning in car navigation in particular can
improve road transport safety,
-
increasingly advanced algorithms are being used in
GNSS positioning in car navigation to improve the accuracy of determining the
position of a moving object,
-
it should be noted that all global GNSS systems are
used on a daily basis in car navigation,
-
GNSS positioning in car navigation involves
integration with other navigation or imaging sensors.
-
single-frequency code-based SPP remains the most
popular solution for GNSS positioning in car navigation [16].
1.2. Research
Problem
With regard to the presented analysis of the state of
knowledge, it can be seen that there is a lack of research on multi-receiver
SPP solutions on one car. This applies to both the GPS navigation system itself
and combinations of systems, e.g., GPS/GLONASS. Furthermore, the use of several
GNSS receivers allows for redundancy in the user's coordinate navigation
solution, which is crucial in kinematic measurements. The more coordinate
determinations there are, the greater the confidence in the user's position. In
addition, it is possible to check the individual readings from each GNSS
receiver. Therefore, the main objective of the study was to determine the
positioning accuracy parameter in car navigation based on a multi-receiver SPP
code solution. In particular, the importance of the combined GPS/GLONASS
solution was emphasized in relation to GPS positioning alone and GLONASS
separately. It was noted that the SPP GPS/GLONASS solution provides better
accuracy than the single determination of SPP GPS or SPP GLONASS. Furthermore,
the research was conducted in kinematic mode for five GNSS receivers mounted on
the roof of a car. The results obtained are interesting for the mass
application of the SPP code method in car navigation.
The article is divided into five main sections: 1.
Introduction, 2. Materials and methods, 3. Research results, 4. Discussion, 5.
Conclusion. In addition, two subsections have been added to Section 1. A
bibliography has also been added at the end of the paper.
2. MATERIALS
AND METHODS
To solve the research problem, a methodology was
developed, the block diagram of which is shown in Fig. 1. At the beginning,
each of the on-board GNSS receivers collects GPS and GLONASS code observations
in real time in kinematic mode every 1 s. The GNSS receivers are designated as
R0, R1, R2, R3, and R4. The receiver R0 is the central receiver, while
receivers R1-R4 are external receivers, as shown in Fig. 2. In addition,
receiver R0 is a Septentrio AsteRx2i receiver [28],
while receivers R1-R4 are Topcon TPS HiperPro
receivers [29]. All GNSS receivers were placed on the roof of the car on a
specially prepared metal structure. Receivers R1 and R2 were positioned
opposite each other, as were receivers R3 and R4. The distance between
receivers R1 and R2, and between R3 and R4, was approximately 1.5 m. Receiver
R0, in turn, was located in the center of the beam
between receivers R1, R2, R3, and R4. For the geometry of all GNSS receivers,
information on the antenna’s phase center
characteristics was used so that the GNSS observations would be referenced to
the antenna’s ARP reference point [30].
Fig.
1. The flowchart of research methodology
Fig.
2. The on-board GNSS receivers
The car performed a test drive in north-eastern Poland
in the Warmian-Masurian Province. The experiment
lasted from 08:03:56 to 09:22:18 in 17.09.2015 according to GPS Time. The
research for this article was conducted at the EPOD airport in Olsztyn. There
were no terrain obstacles, trees, or tall buildings along the car’s route. The
GNSS signal reached the receivers mounted on the car’s roof directly. The speed
was approximately 40 km/h and the route was about 20 km long. During the trip, there were 2 stops totaling about 45 minutes. A sketch of the route is shown
in Fig. 3.
Fig.
3. The rough sketch of the car's route
Based on the attached block diagram, the position of
the car was determined based on GPS and GLONASS observations. Ultimately, the
SPP code method [31] in RTKLIB v.2.4.3. software [32] was used to determine the
coordinates. In RTKLIB software, the processing strategy was configurated as
follow: elevation mask: 5 degree, ionospheric model: Klobuchar
model, tropospheric model: Saastamoinen model, weighting scheme: in function of
elevation angle. The coordinates of the car's
position for each GNSS receiver were determined in three ways, i.e., from the
GPS solution, the GLONASS solution, and the joint GPS/GLONASS solution. Thus,
three sets of BLh geodetic coordinates were obtained
from each GNSS receiver. In addition, the reference position of the car's
trajectory is determined for each GNSS receiver using the PPP measurement
technique [33]. In this case, the calculations were performed on the basis of
code and carrier-phase observations in the CSRS-PPP software [34, 35]. The
reference trajectory of the vehicle from the CSRS-PPP program was determined
with high accuracy, i.e., better than 0.05 m for the horizontal components and
better than 0.09 m for the vertical component. Then, the results of the BLh geodetic coordinates were compared with each other to
determine the position errors [36], as shown in Equations (1-3).
Equations
(1-3) describe position errors for each GPS, GLONASS, and GPS/GLONASS solution
for a single GNSS receiver in the form:
where:
In
turn, for a system of 5 GNSS receivers, the positioning accuracy of the car is
as follows:
where:
In
addition, the RMS statistical error [37] will then be:
where:
Furthermore,
using Equations (6-8), we determined the percentage change in the position
error spread of the GPS/GLONASS solution relative to the individual results
from the GPS and GLONASS solutions:
where:
Equations
(1-8) describe the accuracy of car positioning based on GPS, GLONASS, and
GPS/GLONASS solutions. This gives us three accuracy results for describing the
position of the car's movement. The Scilab v.6.1.1
software was used to calculate the parameters from Equations (1-8) [38]. The
calculation results are shown in Section 3.
3. RESEARCH
RESULTS
The presentation of the accuracy test results obtained
was divided into three parts, i.e., results from the GPS solution, results from
the GLONASS solution, and results from the GPS/GLONASS solution. Within the GPS
solution, the number of GPS satellites tracked by all GNSS receivers was first
shown, as illustrated in Fig. 4. All receivers R0, R1, R2, R3, and R4 tracked
between 8 and 11 GPS satellites while the car was in motion. In the first part
of the experiment, the number of GPS satellites was the highest.
Next, Figs. 5-7 show the individual position error
values
Fig.
4. The number of GPS satellites
Fig.
5. The position errors along B coordinate from GPS solution for each receiver
Fig.
6. The position errors along L coordinate from GPS solution for each receiver
Fig.
7. The position errors along h coordinate from GPS solution for each receiver
The second part of the presentation of results
concerns the GLONASS solution. Fig. 8 shows the number of GLONASS satellites
tracked by all GNSS receivers. All receivers R0, R1, R2, R3, and R4 tracked
between 7 and 10 GLONASS satellites while the car was in motion. The number of
GPS satellites tracked was higher than that of GLONASS satellites during the
experiment.
Fig.
8. The number of GLONASS satellites
Figs. 9-11 show the individual position error values
Finally, the GPS/GLONASS positioning results were
presented. Fig. 12 shows the number of GPS+GLONASS satellites tracked by all
GNSS receivers. All receivers R0, R1, R2, R3, and R4 tracked between 16 and 21
GPS+GLONASS satellites while the car was in motion. In the first phase of the
kinematic test, the number of GPS+GLONASS satellites was the highest.
Figs. 13-15 show the individual position error values
Fig.
9. The position errors along B coordinate from GLONASS solution for each
receiver
Fig.
10. The position errors along L coordinate from GLONASS solution for each
receiver
Fig.
11. The position errors along h coordinate from GLONASS solution for each
receiver
Fig.
12. The number of GPS+GLONASS satellites
Fig.
13. The position errors along B coordinate from GPS/GLONASS solution for
each receiver
Fig.
14. The position errors along L coordinate from GPS/GLONASS solution for
each receiver
Fig.
15. The position errors along h coordinate from GPS/GLONASS solution for
each receiver
4. DISCUSSION
As
part of the discussion, the accuracy results calculated according to Equations
(4-8) were presented. Figs. 16-18 show the position error results
For
the GLONASS solution, the position errors ranged from -3.37 m to 1.54 m for the
B component, from -1.92 m to 3.87 m for the L component, and from -2.82 m to
4.41 m for the h component. For the B component, the spread of maximum position
error results improved by
For
the GPS/GLONASS solution, the position errors ranged from -1.08 m to 0.56 m for
the B component, from -0.26 m to 1.29 m for the L component, and from -3.07 m
to -0.20 m for the h component. For the B component, the spread of maximum
position error results improved by
Fig.
16. The final position errors for BLh coordinates
from GPS solution
Fig. 17. The final position errors for BLh coordinates from GLONASS solution
Fig. 18. The final position errors for BLh coordinates from GPS/GLONASS solution
All
RMS errors are summarized in Table 1. The GPS/GLONASS solution significantly
improved the determination of the ellipsoidal height h compared to the GPS and
GLONASS solutions alone. Furthermore, the GPS/GLONASS solution improved the
determination of all BLh coordinates compared to the
GLONASS solution alone.
Tab. 1
Characteristic
of RMS errors
|
Coordinate |
GPS [m] |
GLONASS [m] |
GPS/GLONASS
[m] |
|
B |
0.21 |
1.34 |
0.34 |
|
L |
0.53 |
1.83 |
0.73 |
|
h |
2.06 |
1.78 |
1.51 |
The discussion also referred to the accuracy results
obtained in relation to the analysis of the state of knowledge. It is worth
noting that the obtained GPS, GLONASS, and GPS/GLONASS positioning accuracy
results meet the standards for car navigation, as shown in publication [12]. In
addition, thanks to the presented research method, it was possible to increase
the accuracy of kinematic positioning of a car, similarly to the works [5,
13-27]. Furthermore, this work uses the SPP code positioning method, as in
works [5, 13-27]. The article is part of a trend in research on the use of
Multi-GNSS observations in kinematic positioning in road transport, as in works
[5, 25]. The research was conducted using only GNSS receivers without
additional sensors or navigation systems, which directly refers to publications
[5, 12, 13, 14, 15, 16, 24, 25].
5. CONCLUSION
The
research conducted confirmed the usefulness of the proposed approach. Based on
the analysis of the results, the following conclusions can be drawn:
-
the multi-receiver SPP solution ensures redundancy of
GNSS measurements, which increases the accuracy of the determined position of
vehicle,
-
the use of a hybrid SPP (GPS+GLONASS) significantly
reduces positioning errors compared to standalone GLONASS, confirming the
higher accuracy of the combined solution,
-
the positioning accuracy achieved (RMS errors at the
level of single meters) is several times better than the required 20 m for car
navigation, which proves that the method meets accuracy standards and is
practical for use in automotive systems,
-
the method based solely on GNSS code observations
(without additional on-board sensors) is simple to implement and attractive for
car navigation systems, thus increasing the safety and reliability of
positioning in road transport.
In
the future, the authors plan to expand their research to include SBAS and DGPS
positioning methods in car navigation. In addition, other GNSS systems, such as
Galileo and BeiDou, will be used for the vehicle's kinematic positioning. This
study did not use the Galileo and BeiDou systems due to the age of the
receivers, which posed a certain limitation to the research. However, in the
future, the authors plan to use all available global GNSS systems for vehicle
positioning.
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Received 24.06.2026; accepted in
revised form 21.09.2026
Scientific
Journal of Silesian University of Technology. Series Transport is licensed
under a Creative Commons Attribution 4.0 International License
[1] Faculty of Navigation and Logistic,
Polish Air Force University, Dywizjonu 303 35 Street,
08-521 Dęblin, Poland. Email: k.krasuski@law.mil.pl.
ORCID: https://orcid.org/0000-0001-9821-4450
[2] Faculty of Navigation and Logistic,
Polish Air Force University, Dywizjonu 303 35 Street,
08-521 Dęblin, Poland. Email: m.bakula@law.mil.pl.
ORCID: https://orcid.org/0000-0002-7180-8483
[3] Faculty of Navigation and Logistic,
Polish Air Force University, Dywizjonu 303 35 Street,
08-521 Dęblin, Poland. Email: p.miduch@law.mil.pl.
ORCID: https://orcid.org/0009-0000-6936-9664