Multi-GNSS precise point positioning for precision agriculture
Multi‑GNSS precise point positioning for precision agriculture
Jing Guo 0 1 2 3 4 5
Xingxing Li 0 1 2 3 4 5
Zhenhong Li 0 1 2 3 4 5
Leyin Hu 0 1 2 3 4 5
Guijun Yang 0 1 2 3 4 5
Chunjiang Zhao 0 1 2 3 4 5
David Fairbairn 0 1 2 3 4 5
David Watson 0 1 2 3 4 5
Maorong Ge 0 1 2 3 4 5
Zhenhong Li 0 1 2 3 4 5
0 German Research Centre for Geosciences GFZ , Telegrafenberg, 14473 Potsdam , Germany
1 GNSS Research Centre, Wuhan University , Wuhan 430079 , China
2 School of Engineering, Newcastle University , Newcastle upon Tyne NE1 7RU , UK
3 School of Agriculture, Food and Rural Development, Newcastle University , Newcastle upon Tyne NE1 7RU , UK
4 Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences , Beijing 100097 , China
5 Earthquake Administration of Beijing Municipality , Beijing 100080 , China
The main objective of this research was to examine the feasibility of MultiGNSS precise point positioning (PPP) in precision agriculture (PA) through a series of experiments with different working modes (i.e. stationary and moving) under different observation conditions (e.g. open sky, with buildings or with canopy). For the stationary test carried out in open space in the UK, the positioning accuracy achieved was 13.9 mm in one dimension by a PPP approach, and the repeatability of positioning results was improved from 19.0 to 6.0 mm by using Multi-GNSS with respect to GPS only. For the moving test carried out in similar location in the UK, almost the same performance was achieved by GPS-only and by Multi-GNSS PPP. However, for a moving experiment carried out in China with obstruction conditions, Multi-GNSS improved the accuracy of baseline length from 126.0 to 35.0 mm and the repeatability from 110.0 mm to 49.0 mm, The results suggested that the addition of the BeiDou, Galileo and GLONASS systems to the standard GPS-only processing improved the positioning repeatability, while a positioning accuracy was achieved at about 20 mm level in the horizontal direction with an improvement against the GPS-only PPP results. In space-constrained and harsh environments (e.g. farms surrounded with dense trees), the availability and reliability of precise positioning decreased dramatically for the GPS-only PPP results, but limited impacts were observed for Multi-GNSS PPP. In addition, compared to real time kinematic (RTK) GNSS, which is currently most commonly used for high precision PA applications, similar accuracy has
been achieved by PPP. In contrast to RTK GNSS, PPP can provide high accuracy
positioning with higher flexibility and potentially lower capital and running costs. Hence, PPP
might be a great opportunity for agriculture to meet the high accuracy requirements of PA
in the near future.
GNSS · Precise point positioning · Real time kinematic
Emerging in the mid-1980s, precision agriculture (PA) is a farming management
concept based on observing, measuring and responding to the spatio-temporal variability in
weather, soil and agricultural production. It involves the employment of appropriate
technologies for the location, in a timely manner and in the right way to improve production
while minimizing environmental impacts
(Gebbers and Adamchuk 2010)
accuracy is of prime importance for precise management of agricultural operations.
Different PA applications require different positioning accuracies
(Perez-Ruiz and Upadhyaya
: (i) low accuracy (meter level) can be used for asset management, tracking and
tracing; (ii) medium accuracy (sub-meter level) can be used for tractor guidance, via
manual control, for lower accuracy operations such as spraying
(Xue et al. 2016)
harvesting bulk crops and for area measurement and field mapping
(Auernhammer et al.
; (iii) high accuracy (cm level) can be used for auto-steering systems on tractors and
self-propelled machines (harvesters and sprayers)
(Gan-Mor et al. 2007; Dijksterhuis et al.
1998; Bell 2000)
and for precision operations such as planting
(Sun et al. 2010; Ehsani
et al. 2004)
. In PA, it is well recognized that Global Navigation Satellite Systems (GNSS)
are the major enabler of ‘precision’ (Larsen et al. 1994;
Krüger et al. 1994
GNSS represents a constellation of satellites providing signals from space,
transmitting positioning and timing data with global coverage. A GNSS receiver employs
trilateration to determine its position on or near the Earth’s surface by timing signals
from four or more GNSS satellites. There are two fully operational GNSS systems at
present—the United States’ Global Positioning System (GPS), and the Russian
Federation’s Global Navigation Satellite System (GLONASS): and two systems under
development—the Chinese Beidou Navigation Satellite System (BeiDou), and the European
Union’s Galileo system, which are both expected to achieve full global coverage
capability by 2020. In addition, the Japanese Quasi-Zenith Satellite System (QZSS) and
Indian Navigation with Indian Constellation (NAVIC) are two regional systems. Over
the past three decades, the US GPS system has been the most accurate and reliable
means for positioning, navigation and timing (PNT) services, and has made great
contributions to earth sciences and engineering applications. Up to now, 32 GPS
satellites consisting of BLOCK IIR, BLOCK IIR-M, and BLOCK IIF are operational and
equally distributed in three independent orbit planes. Unlike previous BLOCK II/
IIA satellites, BLOCK IIF satellites can broadcast a third signal, allowing
acceleration and improvement of the positioning accuracy further. The Soviet Union started
to develop the GLONASS system in 1976. Due to subsequent political and economic
issues, retired satellites were not replaced, resulting in insufficient satellites in orbit
to provide services during the late 1990s and the first decade of 2000s. With a
modernized plan, the constellation has been recovered since 2011. Currently, 24 satellites
are operational to provide PNT services. The new and emerging BeiDou and Galileo
systems provide potential for more precise and reliable GNSS applications and
services around the world, or in certain regions. BeiDou, declared to be operational to
provide regional PNT services in December 2012, consisted then of 5 Geostationary
Orbit (GEO), 5 Inclined Geosynchronous Orbit (IGSO), and 4 Medium Earth Orbit
(MEO) satellites. With the launch of new generation BeiDou IGSO and MEO satellites
in 2015 and 2016, the system is starting to become a global navigation satellite system,
and this phase will be completed in 2020. By then, the space segment of BeiDou will
consist of 5 GEO, 3 IGSO, and 27 MEO satellites
. Galileo is aiming to
provide a highly accurate, guaranteed global positioning service under civilian control.
Its In-Orbit Validation (IOV) phase has been completed, and the system is moving to
the Full Operational Capability (FOC) phase. As part of the IOV phase, 4
GalileoIOV experimental satellites were sent into orbit on 21 October 2011 and 12 October
2012; fourteen FOC satellites have been successfully launched since then. The initial
services started on 15 December 2016, and the full operation of the Galileo
constellation will be accomplished with 30 satellites in three orbital planes in 2020
More than 80 GNSS satellites in total are now in orbit around the Earth, and about 120
satellites will be available once all the four global GNSS systems are fully deployed in
the near future. Increasing the number of operational systems is expected to improve
the observation geometry, which in turn will benefit the positioning accuracy,
availability, integrity and continuity.
It is well known that a common approach to achieve real-time high accuracy
positioning results for a moving device in PA is Real Time Kinematic GPS (RTK GPS),
in which two or more GPS receivers (at least one rover and one reference) track
similar satellites, and both pseudo-range and phase measurements are used to provide up
to centimeter-level positioning accuracy. As the co-ordinates of the reference
stations are known, a range of common errors (e.g. orbital, ionospheric and tropospheric
effects) between the reference and the rover receivers can be estimated and then used
to improve the positioning accuracy of the rovers. Note that the correlation of errors
decreases with increased distance between the reference and rover receivers. The
deployment of two GPS receivers along with a radio data link for agricultural
applications could be expensive in many instances. An alternative, to reduce the cost without
degrading the positional accuracy, is to use Network RTK
(Sun et al. 2010; Gan-Mor
et al. 2007; Dijksterhuis et al. 1998; Bell 2000)
. However, the subscription fee of the
Network RTK service is high, particularly for those seeking centimeter level accuracy.
In contrast to RTK, precise point positioning (PPP) uses dual-frequency pseudo-range
and carrier phase observables from a single receiver, as well as precise satellite
positions and clocks, to determine its absolute co-ordinate at the same level of accuracy as
RTK, but with higher flexibility, potentially lower capital and running costs and global
capability (Zumberger et al. 1997). In this case, no correction from reference stations
is required for PPP, except for precise satellite position and clock products that are
freely provided by the International GNSS Service (IGS)
(Dow et al. 2009)
GPS PPP has not been used in PA, let alone Multi-GNSS PPP, although previous
research has demonstrated that Multi-GNSS can provide higher accuracy and more
stable positioning for PA
(Kabir et al. 2016)
. This paper attempts to examine the
feasibility of multi-GNSS PPP in PA through a series of experiments with different working
modes (i.e. stationary and moving) under different observation conditions (e.g. open
sky, with buildings or with canopy). All operational systems—GPS, GLONASS,
Galileo and BeiDou—were used in this study.
Materials and methods
In order to assess the feasibility of Multi-GNSS PPP for PA applications and evaluate the
performance of Multi-GNSS PPP, three experiments were carried out in different
working modes at different sites (Fig. 1): (i) the stationary (static) experiment, labeled as EPs1,
was carried out on the roof of the Drummond Building of Newcastle University (UK) with
two Leica receivers under the open sky on 2 March 2016; (ii) the first moving (kinematic)
experiment was conducted in Cockle Park Farm of Newcastle University (UK) with three
Leica receivers on a truck on 2 September 2015 (indicated as EPm1 hereafter); and (iii) the
second moving experiment was carried out at Xiaotangshan Farm of the National
Engineering Research Center for Information Technology in Agriculture (NERCITA), Beijing,
China with two Trimble NetR9 receivers on a tractor on 14 September 2015 (labeled as
For EPm1, the truck was systematically driven around a field at Cockle Park Farm
(indicated by a red rectangle, Fig. 1b) from 10:38 (UTC time). About 2 h later, the truck left
the field for a return to the main University campus by a fast southbound route (distance
30 km). On the way, the driver stopped for a break (at the village of Stannington,
indicated by a blue circle in Fig. 1b) during the period from 13:00 to 13:45. For EPm2, the
tractor kept moving and repeated the same bounding route around the Xiaotangshan farm
(Fig. 1c), except for the period from 03:40 to 05:00 (UTC time), when the driver stopped
for a break. There were trees and some huts at the side (or sometimes both sides) of the
route as shown in the inserts of Fig. 1c.
Multi‑GNSS receivers and configuration
Three different types of Multi-GNSS receiver were used in this study, the Leica Viva GS10
and GS15 for EPs1 and EPm1, and the Trimble NetR9 for EPm2. The Leica Viva GS10
receiver is a 555-channel Multi-GNSS receiver and can collect a range of GNSS signals
(GPS L1, L2, L2C, L5; GLONASS L1, L2; BeiDou B1, B2, B3; Galileo E1, E5a, E5b,
Alt-BOC, E6; and QZSS L1, L2, L5, LEX). The Leica Viva GS15 can track similar
multifrequency signals, except for Galileo E6 and BeiDou B3, and has 150 channels. Both Leica
Viva GS10 and GS15 can access the Leica SmartNet service to provide a Network RTK
solution with an accuracy of better than 8 mm + 0.5 ppb for horizontal components. The
Trimble NetR9 has 440 channels to track multi-frequency signals from GPS, GLONASS,
BeiDou, Galileo, and QZSS with RTK capabilities similar to the Leica receivers.
For EPs1, two Leica AS10 antennas connecting separately to Leica Viva GS10
receivers were set up on a steel bar with a fixed inter-antenna distance of 500.0 mm, and a Leica
Viva GS15 antenna was set up in the middle of the bar to provide the Leica SmartNet
(Takac and Lienhart 2008)
, as shown in Fig. 2a. An identical configuration was
also used for EPm1 with a fixed inter-antenna distance of 763.0 mm, but the steel bar was
mounted on a truck, as shown in Fig. 2b. For EPm2, two Trimble R8-4 antennas
connecting to Trimble NetR9 receivers were mounted on a tractor, and the length between the two
anchorage points (called baseline hereafter) was 432.0 mm (Fig. 2c). The specifications
and configurations of the receivers used in this study are listed in Table 1.
Multi‑GNSS precise point positioning (PPP)
Precise point positioning (PPP) is a satellite positioning technique in which dual-frequency
pseudo-range and carrier phase observables from a single receiver, together with precise
satellite orbit and clock products, are used to determine the receiver’s precise position
et al. 1997)
. For PPP, errors from a range of sources including ionospheric delay, tropospheric
delay, receiver clock, multipath and measurement noises need to be carefully handled. In
general, the ‘ionosphere-free’ combination of double frequency measurements is usually formed
to remove the ionospheric delay, and the tropospheric delay and receiver clock offset are
estimated with the site co-ordinates simultaneously. No model is available for removing the
multipath errors, hence it has been left to be absorbed by the post-fit residuals. Other error sources,
such as satellite and receiver antenna phase center variations (PCVs) as well as offsets (PCOs),
relativistic effects, phase wind-up, earth tides, ocean loading and atmosphere loading can be
corrected with appropriate models
(Kouba and Héroux 2001)
. As the site co-ordinates and
receiver clock need to be estimated, a minimum of four measurements are required. PPP can
be conducted globally and is currently able to provide millimeter-level accuracy in a stationary
mode and centimeter-level accuracy in a moving mode
(Li and Zhang 2012)
. PPP has a few
advantages over relative positioning techniques such as RTK: no restriction with inter-station
distances, direct determination of position solution, simple data processing and global
capability. As a result, PPP is widely applied to near real-time meteorology
(Rocken et al. 2005; Lu
et al. 2016)
, crustal deformation monitoring (Calais et al. 2006), orbit determination of low
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As a satellite-based navigation and positioning system, the accuracy and reliability of
GNSS PPP solutions are highly dependent on the number of visible satellites. When using
GPS only, the number of visible satellites is insufficient to provide a position solution under
some situations such as in urban canyons, open-pit mines, mountainous areas and tree cover
areas in agriculture. With the recent revitalization of the GLONASS constellation and two
newly emerging constellations of BeiDou and Galileo, it is now feasible to conduct
MultiGNSS PPP with about 80 operational satellites, increasing the number of visible satellites
The data collected in the above three experiments were analyzed using the PPP approach
with the positioning and navigation data analyst (PANDA) software package
(Liu and Ge
. The analyses were based on the sequential least squares approach
performed independently with GPS-only or Multi-GNSS measurements (GPS, GLONASS,
Galileo and BeiDou). Among the four systems, GPS can provide the best individual solution due
to the larger number of satellites in orbit, as well as the best quality of orbit and clock
products. Hence, in this study, GPS was used to assess the PPP performance of a single system,
whilst a combination of GPS, GLONASS, BeiDou and Galileo was employed to assess the
PPP performance with multiple systems. GNSS data were processed in a post-mission mode,
and the GFZ final orbit and 30 s clock products of IGS Multi-GNSS Experiment (MGEX)
were used. For Multi-GNSS PPP, additional inter-system bias (ISB) and inter-frequency bias
(IFB) parameters also needed to be estimated, as those parameters are used to account for the
signal biases of different GNSS systems or frequencies. Table 2 presents the data processing
strategy in detail.
‘Precision’ and ‘accuracy’ are often used to describe how good the position acquired by
the GNSS actually is. These terms are technically different as ‘precision’ refers to the
closeness to the mean observation and ‘accuracy’ refers to truth. Usually, the precision has been
obtained and is used as no absolute truth is available. In order to assess the accuracy achieved
by PPP, two receivers were set up on the steel bar as described above (Fig. 1) with a fixed,
precisely known, inter-antenna distance in each experiment. After performing PPP for each
receiver, the co-ordinates of each could be obtained to compute the length of the inter-antenna
distance (referred as baseline length hereafter), which can be compared with the truth. Hence,
the Root Mean Square Error (RMSE) and standard derivation (Stdev) of this dataset are used
to describe the accuracy and precision of PPP, respectively in this study.
n − 1 i=1
bi − b̃ 2
bi − bavg
where bi is the derived length of baseline for the epoch i, b̃ is the precisely known
interantenna distance, bavg is the mean of the baseline length, n is the number of epochs. As the
baseline length was obtained by differencing two receivers’ co-ordinates, the RMSE will
be √6 times the 1D accuracy of PPP co-ordinates, given the same errors for 1D PPP
coordinates of the two receivers at either end of the baseline. In addition, as the RTK solution
could be obtained by the Leica Viva GS15 receiver in EPs1, the PPP derived co-ordinates
of the antennae at either end of the bar can also be used to derive the positions of the Leica
Viva GS15 antenna and compare with Leica SmartNet RTK solutions, thus assessing the
precision of PPP.
Results and discussion
Figure 3a shows the number of visible satellites for each GNSS system (i.e. GPS (G),
GLONASS (R), Galileo (E), and BeiDou (C)) as well as the total number of all GNSS
systems (G + R+E + C) for EPs1. Up to three Galileo satellites were tracked, but one was
only observed for a quite short period (about 1 min). Similarly, only two BeiDou
satellites were tracked, as BeiDou provided best coverage in the Asia–Pacific region at the
time of this experiment. Although more than 8 GPS satellites were observed in most
periods of the experiment, there was only one satellite available during the beginning 10 min
(14:54:10–15:04:07). More than 4 GLONASS satellites were tracked, and the number
gradually increased to 7. In sum, no more than 9 satellites were tracked during the first
10 min, and half of them were GLONASS satellites. After that, at least 16 satellites were
observed. Figure 3b shows the PDOP (Positioning Dilution of Precision) values for
positioning with GPS, GLONASS and Multi-GNSS systems. No PDOP of BeiDou or Galileo
is included in Fig. 3b due to the insufficient number of satellites (<4 for both systems).
Similarly, there were no PDOP values for GPS only PPP in the first 10 min, as only one
GPS satellite was tracked. In general, the GPS PDOP values mainly varied between 1.5
and 4 m, while the GLONASS PDOP values were about 2–6 m. However, once all
satellites were used, the PDOP values significantly reduced, to 1.5 m or lower. In particular,
thanks to the contribution from GLONASS, a positioning solution was possible for the first
10 min. These enhancements suggest a definite advantage of Multi-GNSS over a single
system. A high correlation between PDOP and the number of satellites could be easily
observed: the more satellites, the lower PDOP can be.
Three PPP solutions were obtained, by using GPS (GPS-only), GPS and GLONASS
(GPS + GLONASS), and quad-constellation (ALL) measurements for EPs1, respectively.
Fig. 3 The number of tracked
satellites (a) and PDOP (b) for
EPs1. The number of GPS (G),
GLONASS (R), Galileo (E),
BeiDou (C), and all satellites
(G + R+E + C) are shown in
dark blue, blue, cyan, green, and
orange lines, respectively, and
the same for PDOP (Color figure
solution. Figure 5 illustrates the corresponding co-ordinate differences between RTK and
quad-constellation PPP solutions in the east (E), north (N) and up (U) components, and
the statistical results are listed in Table 4. In general, the differences were quite stable,
except for the discontinuity that occurred around 15:53:00 in the up component. This was
caused by the jump in the estimated troposphere delays of PPP, estimated as a piece-wise
constant every 1 h. Once only one troposphere parameter was estimated, the bias
disappeared (Fig. 5b). Systematic biases between the Leica SmartNet RTK and Multi-GNSS
PPP solutions can be observed in both horizontal and vertical components for two reasons.
Firstly, these two solutions were in two different reference frames. The RTK solution was
in the WGS84 frame, whereas the PPP solution was in the IGb08 frame. Secondly, the
unmeasured offset between the reference point of Leica GS15 antenna and mounted point
on the bar biased the solutions. However, once the biases are removed, the two solutions
are in good agreement with Stdev of about 6.0, 7.0, and 32.0 mm in the east, north and up
components, respectively. This further confirms that Multi-GNSS PPP can have a similar
positioning accuracy to RTK, at least in a stationary mode.
This stationary experiment suggests that centimeter level accuracy can be achieved by
the PPP approach. In addition, Multi-GNSS can not only improve the repeatability of PPP,
but also make positioning possible when a limited number of satellites from a single GNSS
system have been tracked.
Multi‑GNSS moving experiments
Like the stationary experiment, Multi-GNSS has positive impacts on improving the
accuracy and reliability of PPP. For EPm1, there were no more than 3 Galileo satellites
observed (Fig. 6). However, up to four BeiDou satellites were tracked throughout most of
the experiment. For the period when the truck was in the field or stopped at Stannington,
at least 6 GLONASS and 7 GPS satellites were observed. However, the number of tracked
satellites varied significantly on the road southwards due to the obstruction of trees and
constructions. In sum, more than 18 satellites could be used for positioning when the truck
was in the field or stopped at Stannington, but most of the GNSS satellites were obstructed
when the truck was on the road. High correlation between PDOP and the number of
tracked satellites was also identified. Similar to EPs1, the smallest PDOP were obtained
once all tracked satellites were used for PPP, whereas it was measured as 1.5–4 m and
2–6 m for GPS and GLONASS-only solutions respectively. Although more than four
satellites were available for the obstruction period, the PDOP values fluctuated significantly and
it was difficult (if not impossible) to determine the co-ordinates even using Multi-GNSS
satellites. Hence, in this study, only the data when the truck was in the field was selected
for further analysis.
Figure 7 shows two PPP solutions for EPm1, one using GPS (GPS-only) and the other
with quad-constellation (ALL) measurements. The corresponding statistical results
presented in Table 3, suggest similar performances for both PPP solutions in general. The
Stdev was only 11.0 mm for both solutions, while the differences of mean values compared
to the true length of baseline were 5.0 mm and 4.0 mm for GPS-only and Multi-GNSS
solution, respectively. The four-system combined solution (12.0 mm) had slightly higher
accuracy than that of the GPS-only solution (13.0 mm). In addition, for the period when
the tractor stopped from about 10:51–11:22, the Multi-GNSS solution showed less
variation and higher accuracy compared with the GPS-only solution.
Whilst experiments EPs1 and EPm1 were carried out in the UK, EPm2 was
conducted in China. Up to 10 BeiDou satellites were tracked, including GEO and IGSO
satellites (Fig. 8). Similar to the other two experiments, both GPS and GLONASS satellites
had good visibility, each with 7 or more satellites, particularly when the tractor stopped
for its break. The total number of all the tracked satellites was up to 26 with periodic
variations, because the tractor repeated the same route and GNSS signals were regularly
obstructed by trees and buildings along the roads in the west and south (Fig. 3c).
However, different from EPm1, at least eight satellites were available to ensure the reliability
Fig. 8 The number of tracked
satellites (a) and PDOP (b) for
EPm2. The number of GPS (G),
GLONASS (R), BeiDou (C),
and all satellites (G + R+C) are
shown in dark blue, blue, green,
and orange lines, respectively,
and the same for PDOP (Color
and robustness of GNSS PPP solutions even in the obstructed period, and the PDOP
was less than 4 m for the Multi-GNSS combined solution.
Two PPP solutions were obtained by using GPS (GPS-only) and Multi-GNSS (ALL)
measurements for EPm2, respectively. The epoch-wise lengths of baseline obtained
are plotted in Fig. 9, and the corresponding statistical results are in Table 3. It can be
seen that the GPS-only solution showed more obvious variation than the Multi-GNSS
solution. Furthermore, many discontinuities can be observed in the GPS-only solutions
when the tractor moved, as the GPS signals were obstructed by the trees and
buildings along the road. Once the Multi-GNSS observations were used, much more stable
results were obtained, and the jumps were reduced significantly with the Stdev
decreasing from 110.0 to 48.0 mm. The difference of mean to the truth of the baseline length
was reduced to 3.0 mm from 62.0 mm by using Multi-GNSS observations. The accuracy
of baseline measurement reached 35.0 mm (equivalent to 20.2 mm (≈ 35.0∕√3 mm)
accuracy in the horizontal direction and 14.3 mm (≈ 35.0∕√6 mm) in 1D) with about 4
times improvement compared to the GPS only solution (126.0 mm). This demonstrates
the superiority of Multi-GNSS PPP over a single system, the accuracy and stability of
positioning could be improved by using such Multi-GNSS signals, particularly with
From the moving test results, Multi-GNSS improved the satellite availability and
then enhanced the accuracy and stability of positioning better than the single-GNSS
PPP, notably where there were obstructions to GNSS satellites such as in
mountainous or highly urbanized areas. In addition, the precision of baseline was also at
centimetre level, which can be compared with that of RTK. Therefore, Multi-GNSS can be
an option for agricultural users for high accuracy requirement applications in precision
In this study, the performance and feasibility of PPP with Multi-GNSS systems in PA
were assessed with one stationary and two moving experiments. The following
concluding remarks can be drawn from this study:
• The number of Multi-GNSS satellites tracked was higher than the single-GNSS under
both stationary and moving conditions.
Fig. 9 The epoch-wise length
of baseline derived from
GPSonly (blue), and Multi-GNSS
(ALL, red) PPP solutions (Color
• Multi-GNSS PPP showed better precision compared to that of PPP with a single GNSS
system where there are obstructions to GNSS satellites.
• Multi-GNSS PPP showed better repeatability in all experiments compared to that of
PPP with a single GNSS system. Hence, it has potential to work in conditions with
• The tests have also demonstrated that an accuracy of better than 20 mm in 1D can be
achieved by GNSS PPP for both stationary and moving conditions. The accuracy can
be compared with that of RTK. However, the accuracy of a RTK solution is dependent
on the distance between the rover and reference station, and the shorter the inter-station
distance, the better position results can be obtained. For RTK GNSS, a dense reference
station network is required to ensure its accuracy and reliability, which will
inevitably increase the infrastructure cost and service fees. In contrast, GNSS PPP only needs
precise orbit and clock products, which can be obtained from IGS or other institutions
freely, and does not require access to observations from reference stations. Hence, PPP
has higher flexibility and lower capital and running cost, and similar accuracy can be
Precise position is demanded in diverse precision agricultural applications. The above
results have demonstrated that centimeter level can be achieved with GNSS PPP. It is
believed that, due to its effectiveness and low cost, PPP will be a great opportunity for
agriculture, meeting the high accuracy requirement in PA in the near future.
Acknowledgements This work is supported by the STFC Newton Agri-Tech programme through three
projects: (i) Exemplar Smart Farming in Newcastle (ii) Exploring the potential for precision nutrient
management in China, and (iii) PAFiC: Precision Agriculture for Family-farms in China (Reference No:
ST/N006801/1). Part of this work is also supported by the UK Natural Environmental Research Council
(NERC) through the LICS project (Ref. NE/K010794/1). The IGS MGEX are greatly acknowledged for
providing the Multi-GNSS data and products. We also appreciate the colleagues in UK and China for
collecting the data.
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
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