Journal of Global Positioning Systems (2006)
Vol. 5, No. 1-2:135-144
RTK Rover Performance using the Master-Auxiliary Concept
N. Brown, I. Geisler and L. Troyer
Networked Reference Stations and Structural Monitoring
Leica Geosystems, Heinrich-Wild-Strasse, Heerbrugg, 9435, Switzerland
Abstract. The Master-Auxiliary Concept, jointly
proposed by Leica Geosystems and Geo++, is the basis of
the soon to be released RTCM 3.0 network messages, the
first industry standard for network RTK. The new
standard, in addition to promoting increased
compatibility and innovation in the industry, offers some
distinct advantages to the end user over the previous
generation of network corrections, such as VRS. With the
Master-Auxiliary Concept complete information on the
prevailing errors sources is made available to the rover,
thereby facilitating the use of more intelligent positioning
algorithms in the determination of the rover’s position.
The net result is an increased robustness of the system
and increased performance in terms of time to fix,
reliability of the ambiguity fix and position accuracy.
Empirical data from both Leica and third party reference
station software and rover receivers is used to
demonstrate the real world benefits of the Master-
Auxiliary Concept in general and the Leica solution in
particular. Clear improvements can be seen when
combining the Leica GPS Spider network RTK software
with the Leica System 1200 GPS receivers, even when
using network correction data at a sampling rate of only
5s.
Keywords. GPS, network RTK, standard, master-
auxiliary concept
1 Introduction
The use of network RTK in GPS surveying offers several
advantages over single base station positioning. For the
rover user, the advantage of network RTK is that he can
confidently operate at greater distances from the nearest
reference station whilst maintaining a high reliability and
accuracy. For the network operator, network RTK allows
the same level of service to be provided with fewer
reference stations. These benefits are achieved by using
multiple reference stations spread over a region to
observe the spatial distribution of the dominant error
sources, namely ionospheric delay, tropospheric delay
and orbit error. These errors, which may be classified as
dispersive (ionosphere) and non-dispersive (troposphere
and orbit) cause a distance-dependant bias in the position
solution. With the additional information from the
network, it is possible to reduce the distance-dependency
thereby providing consistent rover performance across
the network. During its infancy, several approaches to
network RTK have been used, namely that of VRS and
FKP. These approaches have numerous problems or
limitations as described by Brown et al. (2005). Some of
the key problems are:
1. The modelling performed by the network software,
which is proprietary, greatly influences the
information that is provided to the rover. Thus not all
of the relevant information is provided to the rover
prohibiting it from using the optimal processing
techniques for the situation at hand.
2. Proprietary information is transmitted. As such the
corrections formats are non-standard and are biased
towards a particular brand of rovers. They are also
contrary to the philosophy of industry standard from
RTCM.
3. VRS requires a two-way data link, thus limiting the
number of simultaneous users and preventing
broadcast distribution of the corrections.
In order to address these and other limitations of the
earlier approaches to network RTK corrections, Leica
Geosystems has driven the development and adoption of
the Master-Auxiliary Concept (MAC) within RTCM
Special Committee 104. The following section gives an
overview of the master-auxiliary concept and shows how
it addresses the shortcomings of the earlier approaches
mentioned above.
Brown et al. (2005) have shown that the master-auxiliary
network messages offer higher reliability and accuracy
than FKP, VRS and single baseline solutions in a direct
comparison against existing solutions in the market. This

136 Journal of Global Positioning Systems
paper expands on the results of Brown et al. (2005) to
give a deeper insight into the master-auxiliary concept in
general and the Leica GPS Spider solution in particular.
Further analysis of the testing results is made in order to
explain the difference in performance between the
different approaches.
2 The Master-Auxiliary Concept
2.1 Background
In September 2001, Leica Geosystems together with
Geo++ presented a paper titled "Study of a Simplified
Approach in Utilizing Information from Permanent
Reference Station Arrays" (Euler et al., 2001) to the
RTCM SC104. This paper contained a proposal for a
standard for network correction messages that would
overcome the problems of the existing approaches. Since
2001 Leica Geosystems has been a driving force behind
the establishment of a standard for network RTK, which
would be a benefit to the whole surveying industry. The
master-auxiliary proposal put forward by Leica
Geosystems and Geo++ has since undergone refinements
based on input from other manufacturers. At the time of
writing, the master-auxiliary network messages are the
only fully documented non-proprietary proposal for
network RTK messages under consideration by RTCM
SC104 and have remained in their current form for over
one year. Just as NTRIP was in use prior to its formal
acceptance by RTCM as a standard, RTCM 3.0 network
messages are already available with the Leica GPS Spider
reference station software and the Leica System GPS
1200 products. Official acceptance and release of the
standard is pending the completion of an interoperability
test sanctioned by RTCM and currently in progress
between the major manufacturers.
2.2 Concept Overview
The basic principle of the master-auxiliary concept is to
provide, in compact form, as much of the information
from the network and the errors it is observing to the
rover as possible. With more information on the state and
distribution of the dispersive and non-dispersive errors
across the network, the rover is able to employ more
intelligent algorithms in the determination of its position
solution. Since each supplier of reference station software
will have their own proprietary algorithms for modelling
or estimating these error sources, to make a standard it is
necessary to divide the computation into the following
steps:
1. Transmission of data to the network processing
centre. Raw code and phase data from each
reference station is collected at a processing facility
together with supporting information such as precise
ephemeris, IONEX and DCB data.
2. Network ambiguity resolution. The phase ranges
from all reference stations are reduced to a common
ambiguity level (Euler et al., 2001). Two reference
stations are said to be on a common ambiguity level
if the integer ambiguities for each phase range
(satellite-receiver pair) have been removed (or
adjusted) so that when double differences are formed
the integer ambiguities cancel. In order to be able to
resolve these network ambiguities, the reference
station software must model or estimate all relevant
error sources, such as satellite and receiver clocks,
ionosphere, troposphere and orbit errors.
3. Site selection. A subset of the stations in the network
is selected that will be used to generate the
corrections for the rover. With two-way
communications, this can be done by the reference
station software, which can select the optimal set of
sites that gives the best solution for the rover whilst
minimising the amount of data to be transmitted.
With broadcast communications the set of sites can
be pre-defined by the network operator.
4. Formation of the network messages. The master-
auxiliary correction differences are formed using the
phase observations of the selected reference stations,
corrected only by the estimated network ambiguities,
the common part of the receiver clock and known
values (geometric range and satellite clock). Thus,
the messages are not influenced by proprietary
modelling or estimation algorithms used by the
network processing software in order to resolve the
network ambiguities. A highly compact message
format is used to minimise the bandwidth that is
required to transmit the corrections (Euler et al.,
2001). To help reduce the amount of data to transmit,
one of the reference stations assumes the role of the
master station for which the full observations are
transmitted. Between-station single differences are
then used to create the correction differences that are
transmitted for the other (auxiliary) stations. For
convenience, the master station is usually chosen as
the station closest to the rover. Note however that the
distance of the master station to the rover has no
bearing on the accuracy of the subsequent
interpolation (step 6 below), since it plays no special
role in the calculation.
5. Transmission of the corrections. The network
messages are transmitted from the reference station
software to the rover using any of a wide range of
two-way or broadcast communication mediums.
6. Localisation of the errors to the rover’s position.
The rover uses the information provided by the

Brown et al.: RTK Rover Performance using the Master-Auxiliary Concept 137
network to determine the dispersive and non-
dispersive errors at its location. A typical approach is
to use an interpolation algorithm, such as the
Distance-Based Linear Interpolation Method (Gao et
al., 1997; Dai et al., 2003; Euler et al., 2004), Low-
Order Surface Model (Dai et al., 2003; Euler et al.,
2004; Wanninger, 2000; Fotopoulos & Cannon,
2001) or Least-Squares Collocation Method (Raquet,
1998; Marel, 1998; Raquet and Lachapelle, 2001;
Alves, 2004). Since this localisation is done on the
rover, unlike with VRS, it is possible to broadcast the
corrections.
7. Determination of the rover’s position. The rover
resolves its ambiguities and determines its position
using the full information of the reference network.
By following this process it is possible to utilize the
information provided by the network to full benefit whilst
having a standard, open format and a process that is
seamless for the rover user. Conceptually, the main
difference between MAC and the other approaches is that
it shifts some of the intelligence from the reference
station software onto the rover. The practical advantages
and implications of this shift are discussed in the
following section.
3 Master-Auxiliary Concept in Practice
3.1 Optimal Site Selection
A reference station network may comprise between three
and one thousand or more reference stations. Depending
on the size of the network and the capacity of the
supporting IT infrastructure it may be necessary to
distribute the processing across two or more servers. In
such a case the network may be divided into clusters.
Each cluster contains a subset of the overall network,
usually with some stations overlapping with adjacent
clusters, and is processed as a single solution (Figure 1).
Due to the broad geographical region typically covered
by a cluster, not all of stations will be able to provide
relevant correction information to a rover at any given
location in or near the cluster. This is because the
ionospheric and tropospheric errors that network RTK is
trying to model are spatially correlated and so stations
that are a long way from the rover (e.g. more than 50-
100km depending on the location and characteristics of
the network) will be influenced by substantially different
atmospheric conditions. Hence, it does not make sense to
use all stations in a network or cluster to generate
corrections for the rover. For this reason, Leica GPS
Spider uses the concept of cells. A cell is a subset of
stations that is chosen based on certain criteria to be the
optimal set of stations to provide MAC corrections to the
rover.
The method of site selection for a cell that is used
depends on the communication technology that is used.
In the case of two-way communications, Leica GPS
Spider will automatically select the optimum set of sites
for the cell used to generate master-auxiliary corrections
for each rover. This correction service is referred to as
Auto-MAX. By choosing the most appropriate cell
configuration, Auto-MAX corrections minimise the
bandwidth required to transmit the corrections. The
master station is always chosen as the station nearest to
the rover. The auxiliaries are chosen from the
surrounding stations to provide the best possible set of
corrections for the rover’s position. With Auto-MAX
even the largest reference networks can be fully serviced
with a single communication channel.
For broadcast communication mediums, pre-defined
cells, which may be created manually by the network
operator, can be used to transmit master-auxiliary
corrections, known as MAX, to the rovers. The rover user
can connect to the correction service that is most relevant
for their geographic location. Depending on the size of
the network, multiple cells can be defined to optimise the
transmission of data by reducing the number of stations
that are contained in the correction messages.
Figure 1. A reference station network comprising a number of clusters.
Network i
Cluster 2
Cluster 1
Cluster N

138 Journal of Global Positioning Systems
Figure 2. A cluster providing master-auxiliary corrections to several
rovers, with each rover using an appropriate cell based on its location.
3.2 Rover Use of the Network Corrections
Since the corrections differences transmitted in the MAC
network messages are ambiguity levelled, the rover is
able to directly calculate the influence of the ionosphere,
troposphere and orbit at its location. Hence, the rover
does not need time for models or estimates of the errors
to converge, unlike the network processing software
(which must resolve the network ambiguities). The
combined influence of the troposphere and orbit can be
calculated for each satellite and each reference station
using the ionosphere-free linear combination and then
interpolated for the rover’s position. Similarly, the
influence of the ionosphere can be calculated for each
satellite and each reference station using the geometry-
free linear combination and then interpolated for the
rover’s position. Thus, high accuracy positioning is
possible from the moment the first set of corrections is
received.
3.3 Update Rate of the Network Corrections
Update rates of 1s are supported for both the master
station observations and the dispersive and non-
dispersive errors. Update rates for the dispersive and non-
dispersive errors can be configured to be slower than 1s
to conserve bandwidth. In the mid-latitudes, the rate of
change of the differential ionosphere is usually less than a
few millimetres per second and corrections should be
updated at least at 10s (RTCM66, 2002). According to
RTCM66 (2002), experience has shown that under
normal operating conditions an update rate of 2-10s for
the dispersive component is sufficient to achieve full
accuracy at the rover. A lower rate of 10-30s may be used
for the non-dispersive component, which changes more
slowly (RTCM66, 2002). Therefore, having an update
rate (of say 2s or 5s) for these corrections will not
significantly impact on the accuracy of the rover’s
position. Table 1 shows the bandwidths that are required
to transmit different corrections. Clearly, MAX
corrections with a update rate of 1s for the master
observations and 2s for both the dispersive and non-
dispersive network messages uses a similar bandwidth to
VRS even though it is transmitting considerably more
information. Note that just because VRS is transmitting at
1s does not mean that the network corrections are being
updated at that rate. If the network processing software
must do the interpolation of the network data at 1s in
addition to the network ambiguity resolution, file
archiving and other tasks, it would run into performance
problems when many rovers are connected. With MAC,
the processing load is distributed between the reference
station software and the rover and so is more efficient.
In the following sections a performance comparison is
made between single baseline, MAX and other network
correction formats. It should be noted that MAX used an
update rate of 5s for the network corrections and still
gave clearly superior performance to VRS and FKP.
Table 1. Bandwidths for network corrections.
Number of Auxiliary Stations
Format
6 8 10
VRS, RTCM 2.3 18/19, 1s
update rate
3776bps# 3776bps# 3776bps#
i-MAX, RTCM 3.0 1004, 1s
update rate
1391bps 1391bps 1391bps
MAX, RTCM 3.0 1017, 1s
update rate for master and
network corrections
5255bps 6567bps 7879bps
MAX, RTCM 3.0 1017, 1s
update rate for master and 2s for
network corrections
3287bps 3943bps 4599bps
MAX, RTCM 3.0 1017, 1s
update rate for master and 5s for
network corrections
2106bps 2368bps 2631bps
# This value does not include the variable length type 59 proprietary
information message, so the actual bandwidth may be higher.
3.4 Legacy Rover Support
The full observations for the master station are
transmitted in the normal RTCM 3.0 1003/1004 message.
Hence, a rover that is able to understand RTCM 3.0 but
not the network corrections is still able to use the
correction stream. For older rovers, Leica GPS Spider
provides an individualised version of the master-auxiliary
corrections, known as iMAX, that may be transmitted
using older versions of RTCM. A performance
comparison of iMAX with the other correction formats is
given in the following section.
Cluster N
Cell 1
Cell 2
Cell
M

Brown et al.: RTK Rover Performance using the Master-Auxiliary Concept 139
4 Performance Comparison
4.1 Test Setup
In order to assess how the advantages of the Master-
Auxiliary Concept translate into benefits for the user,
data was collected from Leica’s RTK testbed. Figure 3
gives an overview of the network setup. The network
consists of 5 stations in the border region between
Switzerland, Austria and Germany. Each station is
equipped with a dual-frequency GPS receiver and is
permanently connected to the Leica office via a broad-
band internet connection. German, Swiss and Austrian
surveying authorities operate the stations. This network
does not represent an unrealistic, idealized showcase
network, but reflects rather challenging conditions:
besides featuring a mix of different receiver and antenna
makes and models, the reference station separations are
up to almost 100km. Especially challenging is the height
separation among the stations: the lowest station
(Uznach) is at an elevation of 475m, whereas the station
Kops is more than 1900m above sea level.
Figure 3. Overview of the test network.
Leica SpiderNet was used to calculate single site, MAX
and iMAX corrections in RTCM 3.0. The MAX
corrections were based on an update rate of 5s for the
dispersive and non-dispersive components of the network
corrections. A third-party network RTK software package
was used to generate FKP and VRS corrections. All
network corrections were based on the same five stations
and were processed simultaneously. The single baseline
corrections were taken from station Kops. The rover
antenna was located at the Leica office at a height of
474m, where the five receivers in Table 2 were connected
to the same rover antenna. The distance from the rover
antenna to the closest reference station, Ravensburg, was
43 km. The distance to the master station Kops, which
was deliberately chosen to be further away to show that
the choice of the master station is not critical for the rover
performance, was approximately 60km with a height
difference of 1500m.
This test ran for several months allowing the first true
long-term statistical analysis of rover performance when
using Master-Auxiliary corrections. The following
sections present typical results from a representative 16h
time window of these long-term measurements.
Table 2. Overview of the receivers and correction formats that were
used in the test.
Receiver RTK Correction
type
RTK Format
Leica GX1230 #1 Single baseline
(Kops)
RTCM v.3.0
Leica GX1230 #2 i-MAX RTCM v.3.0
Leica GX1230 #3 MAX RTCM v.3.0
Leica GX1230 #4 FKP RTCM v.2.3
Third-party receiver VRS RTCM v.2.3
4.2 Availability and Time to Fix
The productivity of a GPS field crew however depends
mainly on the availability of fixed ambiguities (Richter
and Green, 2004). Figure 4 summarizes the percentage of
epochs with RTK fixed, differential code and navigation
solutions that were achieved over the test period. MAX
and iMAX show very similar values and show a better
performance to other network RTK formats. The single
baseline with a Leica rover is in terms of productivity on
a similar level as MAX and iMAX, however in this case
the field crew would of course not benefit from the gain
in accuracy demonstrated in the following section.
Figure 4. Percentage of fixed solutions.
The test and analysis presented so far simulated a rover
occupying a point permanently for 16 hours without
interruptions, and thus re-initialisations were only
necessary in case of loss-of-locks or interruptions of the
correction streams. To achieve results as realistic as
possible, a further test was performed which forced the
Leica receivers to continuously re-initialise (a full reset of
the ambiguity filter) immediately after fixed ambiguities
were attained. If no initialisation was achieved after three
minutes, a new reset was forced. As the third-party rover
did not allow an automated ambiguity reset, it was not
included in this test.

140 Journal of Global Positioning Systems
Figure 5 includes both the number of RTK fixes within a
certain time-to-fix interval, as well as the total number of
ambiguities and confirmation of ambiguities. A higher
number of restarts indicates a higher availability and
reliability and is in fact the most important factor in terms
of productivity gain.
Figure 5. Time-to-fix (TTF) and ambiguity verification (logarithmic
scale).
All three network RTK formats have a higher number of
fixes within the first 22 seconds than the single baseline.
The single baseline is close in this interval, however its
overall number of fixes is significantly lower. If the
ambiguities of the single baseline cannot be resolved in
the first minute, the conditions are not improved by
extending the search period due to significant
atmospheric biases. In a few cases the network results
can be improved by extending the search period, which
proves that the corrected reference observations are more
consistent and may enable ambiguity resolution in
conditions where single baseline would not be possible.
Among the network RTK formats, MAX and iMAX
perform at a similarly high level. FKP shows an almost
equal percentage of fixes within 22 seconds, but has 15%
fewer restarts.
4.3 Precision and Accuracy
One measure of RTK performance is to compare the
accuracy of the measured RTK position with the ground
truth. The NMEA GGA positions from each receiver
listed in Table 2 were used to determine precision and
accuracy estimates for the different network RTK
formats. This paper will focus on analysis of the height
component, since it is the most difficult component in
GPS positioning. For a more detailed analysis of
horizontal position results and for kinematic tests, the
reader is referred to Brown et al. (2005). Figure 6 shows
the height precision of a MAX solution compared to a
single baseline. The results of the MAX data show
noticeable benefits. In the 60km single baseline there are
a significant number of outliers above 15 cm, but none
when using the network solution. The network
information for the troposphere and ionosphere also
improves the precision of the height results.
Figure 6. Height histogram from single baseline and MAX corrections
Figure 7. Height histogram from different network RTK corrections
However, differences can also be seen between different
network RTK formats (Figure 7). As expected, MAX and
i-MAX show very similar values. The VRS corrections,
which were processed by the third-party receiver, show a
significantly lower precision. In addition, a high number
of wrong fixes caused a bias in the average height seen as
a shift in Figure 7.
In order to demonstrate why MAX is able to give
superior performance two periods of time (A and B) will
be analyzed in more detail. Time period A covers
approximately ninety minutes starting at 7:35am local
time. Time period B also has a duration of approximately
ninety minutes but starts at 9:35 pm local time, not long
after sunset. The residual dispersive (ionosphere) and
non-dispersive (troposphere and orbit) errors after double
differencing and application of standard tropospheric
(Modified Hopfield) and ionospheric (Klobuchar) models
where calculated. Since for this test the rover and
reference station coordinates were known is was possible
to determine this error directly by removing the integer
ambiguities. These residuals over time period A are
shown in Figures 8 and 9 for the single baseline solution
and in Figures 10 and 11 for the MAX solution. The
residuals are displayed in units of L1 cycles.

Brown et al.: RTK Rover Performance using the Master-Auxiliary Concept 141
Figure 8. Double difference residual dispersive error for the single
baseline solution during time period A.
Figure 9. Double difference residual non-dispersive error for the single
baseline solution during time period A.
Figure 10. Double difference residual dispersive error for the MAX
solution during time period A.
Figure 11. Double difference residual non-dispersive error for the MAX
solution during time period A.
Both the dispersive and non-dispersive errors are reduced
by the MAX corrections. Some residual error remains,
notably on the double difference pair G13-G2 that could
not be modeled. The low elevation (10 to 14 degrees)
satellite G16 was not fixed by the network. The position
results during this time are shown in Figures 12 and 13 as
time series plots of the difference between the receiver’s
position solution and the known coordinate in easting,
northing and height. The number of satellites used in the
position solution is also displayed. Only RTK fixed
positions have been plotted. For comparison Figures 14
and 15 show the results from VRS and FKP respectively.
The single baseline solution was accurate around GPS
second of week 457500 when it had some troubles fixing
the ambiguities, indicated by the changing number of
satellites used in the solution. No apparent reason for this
can be seen in the residuals. All network solutions gave
consistent performance over the entire period. The
difference in the number of satellites used in the MAX
and VRS/FKP solutions is due to the difference reference
station software.
Figure 12. Difference from the known position for the single baseline
solution during time period A.
Figure 13. Difference from the known position for the MAX solution
during time period A.

142 Journal of Global Positioning Systems
Figure 14. Difference from the known position for the VRS solution
during time period A.
Figure 15. Difference from the known position for the FKP solution
during time period A.
Note that the single baseline used consistently more
satellites in its solution than any of the rovers using
network corrections. This higher availability of satellites
can, in some cases, enable the single baseline solution to
match or even outperform a network solution.
The residual error graphs for time period B, over which
the atmosphere is clearly more active, are shown in
Figures 16 and 17 for the single baseline and Figures 18
and 19 for the MAX solution.
Figure 16. Double difference residual dispersive error for the single
baseline solution during time period B.
Figure 17. Double difference residual non-dispersive error for the
single baseline solution during time period B.
Figure 18. Double difference residual dispersive error for the MAX
solution during time period B.
Figure 19. Double difference residual non-dispersive error for the MAX
solution during time period B.
A much more significant improvement is seen in the
reduction of the dispersive and non-dispersive errors by
MAX during time period B. Some systematic dispersive
error remains indicating that the ionospheric error was
distinctly non-linear over the network. The network had
difficulty maintaining the ambiguity fix for satellites G30
and G3. Satellite G18 was not fixed at all by the network
during this time period. Thus this dataset represents a
difficult situation for the network processing. Figures 20

Brown et al.: RTK Rover Performance using the Master-Auxiliary Concept 143
through 23 show the accuracy of the rover’s position over
time period B for the single baseline, MAX, VRS and
FKP solutions respectively.
As before, the single baseline uses overall more satellites
in its solution than any of the network solutions.
Interestingly the performance of the single baseline
during time period B is similar to time period A in spite
of the higher errors. The high ionospheric error is not
seen in the position solution, which is based on the
ionospheric-free linear combination for such long
baselines. Surprisingly the single baseline solution was
able to maintain a correct ambiguity fix over this time,
which is a credit to the stochastic modeling and repeated
search process used by the Leica rover (see Euler and
Ziegler, 2000).
Whilst the MAX solution uses fewer satellites, the
position solution is more accurate than that of the single
baseline due to the reduced non-dispersive error. The
VRS and FKP solutions also used fewer satellites than
the single baseline, though slightly more than MAX.
However, both the VRS and FKP solutions had difficulty
over this period and actually gave lower accuracy than
the single baseline. This is largely due to the fact that the
VRS and FKP corrections are based on the error
estimates from the state vector of the reference station
software, rather than the actual error as used by MAX. In
the case of VRS, the rover is tricked into thinking that the
baseline is short so it did not use an ionospheric-free
position solution, which would have removed the
ionospheric error that could not be modeled by the
corrections. Even though the MAX solution is using an
update rate of only 5s for the network corrections
(remember that the observations of the master station are
always sent at a 1s rate), it clearly outperforms VRS and
FKP.
These results also demonstrate, by the mix of reference
station software and rovers that were used with the VRS
and FKP solutions and the resulting poor performance,
that one network solution is not the same as another. VRS
and FKP use proprietary information that is not available
to all rovers. By using an open standard such as the
master-auxiliary concept based RTCM network
messages, it is possible to make a level playing field by
removing the manufacturer dependence and compatibility
issues of the other approaches. With an open standard all
rovers have an equal access to the correction data,
thereby maximizing the benefit of the reference network
for all users.
Figure 20. Difference from the known position for the single baseline
solution during time period B.
Figure 21. Difference from the known position for the MAX solution
during time period B.
Figure 22. Difference from the known position for the VRS solution
during time period B.
Figure 23. Difference from the known position for the FKP solution
during time period B.

144 Journal of Global Positioning Systems
5 Conclusions
The Master-Auxiliary Concept, the basis for the
forthcoming RTCM standard for network RTK
corrections, is a revolutionary new approach to network
RTK that addresses the limitations of earlier approaches.
The MAC based RTCM network messages offer an open
standardized format that enables efficient and accurate
network RTK in both broadcast and two-way mode with
out the need for proprietary messages and thus avoiding
the compatibility issues of the earlier approaches. This
paper has explained the principles and practical
application of the Master-Auxiliary Concept. Empirical
data was used to demonstrate the benefits of MAC for the
rover user in terms of increased accuracy, performance
and reliability, even though an update rate of only 5s was
used for the network corrections. The statistical analysis
of all tests clearly showed that the best performance was
achieved by combining Leica GPS Spider with Leica
GPS 1200 rovers utilizing MAX corrections. The
individualized version of the MAX, known as iMAX,
which is also available from the Leica GPS Spider
reference station software gives a similar high level of
performance as MAX but with the advantage of using a
lower bandwidth single site RTCM 2.3 or 3.0 format that
can also be interpreted by older receivers that do not
support the new network messages.
Acknowledgments
The authors thank SAPOS (Germany) and APOS
(Austria) for providing real-time data from their reference
station networks.
References
Alves P.R.S. (2004) Development of Two Novel Carrier Phase-
Based Methods for Multiple Reference Station
Positioning. PhD Thesis, December 2004, University of
Calgary, Alberta, Canada.
Brown N., Keenan R., Richter B. and Troyer L. (2005)
Advances in ambiguity resolution for RTK applications
using the new RTCM V3.0 Master-Auxiliary messages.
In: Proc of ION GNSS 2005, Long Beach, California,
September 13-16, 2005.
Dai L., Han S., Wang J., Rizos C. (2003) Comparison of
Interpolation Algorithms in Network-Based GPS
Techniques. Journal of The Institute of Navigation, Vol.
50, No. 4, Winter 2003-2004, USA.
Euler H.-J., Keenan C.R., Zebhauser B.E. and Wuebbena G.
(2001) Study of a Simplified Approach in Utilizing
Information from Permanent Reference Station Arrays.
In: Proc of ION GPS 2001, Salt Lake City, Utah,
September 11-14, 2001. http://www.leica-
geosystems.com/s-
e/en/downloads/lgs_page_catalog.htm?cid=2702
Euler H.-J., Seeger S., Zelzer O., Takac F., Zebhauser B.E.
(2004) Improvement of Positioning Performance Using
Standardized Network RTK Messages. In: Proc of the
Institute of Navigation National Technical Meeting, ION
NTM 2004, San Diego, California, January 26-28, 2004,
http://www.leica-geosystems.com/s-
e/en/downloads/lgs_page_catalog.htm?cid=3228
Euler H.-J. and Ziegler C. (2000) Advances in Ambiguity
Resolution for Surveying Type Applications. In: Proc of
ION GPS 2000, Salt Lake City, Utah, September 19-22,
2000.http://www.leica-geosystems.com/s-
e/en/downloads/lgs_page_catalog.htm?cid=2702
Fotopoulos G. and Cannon M.E. (2001) An Overview of Multi-
Reference Station Methods for Cm-Level Positioning.
GPS Solutions, Vol. 4, No. 3, pp. 1-10, 2001
Gao Y., Li Z., McLellan J.F. (1997) Carrier Phase Based
Regional Area Differential GPS for Decimeter-Level
Positioning and Navigation. In: Proc of the National
Technical Meeting of the Satellite Division of the Institute
of Navigation, ION GPS 1997, Kansas City, Kansas,
September, 1997, pp. 1305-1314
Marel H. van der (1998) Virtual GPS Reference Stations in the
Netherlands. In: Proc of ION GPS 1998, Nashville,
Tennessee, September 15-18, 1998, pp. 49-58
Raquet J.F. (1998) Development of a Method for Kinematic
GPS Carrier-Phase Ambiguity Resolution Using Multiple
Reference Receivers. PhD Thesis, May 1998, University
of Calgary, Alberta, Canada.
Raquet J.F., Lachapelle G. (2001) RTK Positioning with
Multiple Reference Stations. GPS World, April 2001.
Richter B. and Green A. (2004) Relevance of Dual Frequency
Surveying System Tests for Real Time Field
Performance, In: Proc of ION GNSS 2004, Long Beach,
California, September 21-24, 2004.
RTCM66 (2002) Network RTK Format Proposal for RTCM-
SC104 Version 3.0 by Trimble Navigation, RTCM paper
066-2002-SC104-281-TRIMBLE NETWORK RTK
FORMAT PROPOSAL
Wanninger L. (2000) Präzise Positionierung in regionalen
GPSReferenzstationsnetzen, PhD Thesis, published by
„Deutsche Geodätische Kommission“, series C, booklet
508, Munich 2000, Germany.