How well does the Virtual Reference Station (VRS) System of GPS Base Stations Perform in Comparison to Conventional RTK? G Ong Kim Sun P Gibbings Faculty of Engineering and Surveying University of Southern Queensland TOOWOOMBA QLD 4350
[email protected] ABSTRACT In response to the recent growth in multiple reference station networks throughout the world, a pilot project of the Virtual Reference Station (VRS) network has been established in south-east Queensland. Independent testing of this network was required to establish its performance in post processed and realtime positioning, and its reliable coverage area. Tests were conducted at several sites, both inside and outside the network. GPS data from a single antenna was used to simultaneously record real-time positions derived from both the VRS base stations and a conventional base station. This data was analysed in terms of accuracy, precision and initialisation times. At the same time, raw data was logged for later analysis of the post processing capabilities of the VRS. Accuracy and precision estimates from the data collected showed that the VRS is at least comparable to, and in some instances may be considered superior to, conventional RTK. For example, during tests when low numbers of satellites were visible, the VRS-RTK was able to initialise in shorter times than conventional RTK. In general, the VRS-RTK proved to be a reliable substitute for conventional RTK using a single base station. In fact, VRS-RTK was shown to be more reliable and robust than conventional RTK, and in many instances was able to produce results where conventional RTK failed. VRS also showed great potential for post processing that, until now, has been largely ignored.
INTRODUCTION The Virtual Reference Station (VRS) system is one of many multiple reference station networks operational throughout the world that provide corrections for GPS users. VRS, which was designed to overcome some of the limitations and problems associated with standard or conventional RTK (ClassicRTK), is intended to enable rover receivers to be positioned in real time anywhere within the network of base stations with an accuracy of a few centimetres. VRS uses multiple reference stations whereas Classic-RTK typically uses a single reference (or base) station. Research has found that multiple reference station networks enjoy several advantages over Classic-RTK including a larger service area coverage, increased robustness, and higher positioning accuracy (Hu et al., 2003). A pilot VRS project, the first of its kind in the southern hemisphere (Higgins and Talbot, 2001), has been established in the south-east corner of Queensland. Currently there are four VRS stations in operation in this test area. It has been recognised that limited research has been conducted on the distribution of RTK corrections to real-time users of multiple reference station systems (Hu et al., 2003). This area is regarded as critical to the implementation and acceptance of multiple reference station networks such as VRS. Consequently, the primary purpose of the testing was to assess the accuracy, precision, and time required to solve ambiguities (initialisation time) of the VRS-RTK system. As a secondary consideration, an attempt was made to assess the effective coverage area of the VRS system, and its reliability for post processing.
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The fundamental concept used for this testing was to assess the performance of the VRS-RTK system in comparison to the Classic-RTK with a single base station. During these tests, Classic-RTK and VRSRTK data were collected simultaneously from a single GPS antenna to ensure that, as far as was possible, the Classic-RTK and VRS-RTK experienced the same physical conditions, at the same time. Information on the real-time positioning capabilities of the VRS will be useful for potential users in both government and industry including: surveying firms, local authorities, road and railway authorities, and contractors in the earthmoving, mining, and agriculture sectors. It will also be beneficial to potential users of the VRS to have some estimate of how rapidly the real-time positioning quality degrades as the rover moves outside the boundaries of VRS network of reference stations.
BACKGROUND Classic-RTK lacks data redundancy due to the use of a single base station (Hu et al., 2003), and has the further limitation that observations must be taken within 10 to 20 km of the base station. On the other hand, multiple reference station systems such as VRS are said to enable high-precision positioning over longer distances (Lachapelle et al., 2000). To use the VRS in real time, the user of a rover receiver makes a mobile telephone call to a central processing facility and supplies all necessary data, including its approximate geographic position, via a GSM mobile telephone modem. The central processing facility uses data from all reference stations to model the spatial errors and generate appropriate corrections as if there was a reference station at the rover’s geographic coordinates. The necessary RTK corrections are then sent back to the user’s GPS receiver via the same mobile telephone modem. These corrections are designed to differentially correct positions and to reduce or eliminate the spatially correlated errors such as due to satellite orbit and atmospheric biases. These corrections allow the rover to position itself relative to this virtual reference station assumed to be at the rover’s geographic coordinates. Note that corrections are generated from a virtual reference station as opposed to a physical reference station. Obviously the reliability of the coordinates of the VRS reference stations are of critical importance to the accuracy achieved when using the VRS network. In the case of the VRS used during this testing, the network includes the three to five kilometre density network of existing control stations observed, adjusted, and accepted by the Department of Natural Resources, Mines and Energy (NRM&E) in Queensland. These coordinates have been accepted as error free for the purposes of this research. It has been stated that due to the increased redundancy using multiple reference station technology such as VRS, users should gain greater confidence in the resulting rover positions (Higgins and Talbot, 2001). Results of initial testing conducted on the pilot project in south-east Queensland produced some initial estimates of accuracy (32mm horizontal), precision and initialisation times (less than 1.7 minutes with 5 or more satellites). Similar results (3cm horizontal accuracy and less than 2 minutes initialisation times) were achieved from recent testing of the Singapore Integrated Multiple Reference Station Network (SIM-RSN) using Trimble 5700 and 4700 receivers and Zephyr antennas (Hu et al., 2003). Likewise, results of tests in southern Germany revealed accuracy of a few centimetres (Retscher, 2002), results of tests in Switzerland revealed horizontal accuracy of less than 25mm horizontal and 40mm vertical at the 80 percent confidence level (Brockmann et al., 2001), and similar results were obtained in tests conducted in southern Finland (Santala and Totterstrom, 2002). It should be noted that the preliminary testing of the VRS pilot project in south-east Queensland focussed partly on deliberately trying to defeat the system and to test at limits beyond those recommended by the manufacturers (Higgins and Talbot, 2001). These researchers recommended further testing using typical configuration with rover stations inside the network and all of the VRS reference stations operational as base stations. They also recommended more testing to better measure the effect of moving outside the triangle. This preliminary testing of the VRS needs to be supplemented by rigorous testing and analysis under conditions that might be expected during normal operations. Information is needed on how well the VRS operates in post-processing mode, how well the VRS performs in real time in comparison to conventional
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or Classic-RTK, and how much VRS-RTK accuracy and precision degrade as the user moves outside the network area.
TEST METHOD While the emphasis was on testing the real-time capabilities, an indication was also required of how well the VRS performed for post-processing. Another of the objectives of this research was to consider the performance of the VRS system of the rover located in different geographic areas in relation to the network of base stations. A series of tests were designed to enable an analysis of the VRS with respect to accuracy, precision, initialisation (or time to first fix – TTFF) and coverage (as a secondary consideration). Site selection Fifteen test sites, whose approximate locations are highlighted in Figure 1, were selected for this research. Figure 1 also shows the extent of the VRS at the time of the testing.
Figure 1. Location of test points relative to VRS Network
These test sites were selected, as they were considered indicative of locations where everyday surveying might occur. Ten of the fifteen points had known (published by NRM&E) coordinate values for both the horizontal and vertical component. To assess the coverage area performance of the VRS system, test sites were located inside the network, in areas near or on the boundaries of the network, and outside the network. One site was approximately 6km outside the VRS network boundary, and two were located approximately 10.5km off the VRS network boundary. This distance was measured orthogonally from the triangle boundary formed by straight lines between the VRS reference stations. The equipment at each test site consisted of:
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• • • • •
3 x 5700 Trimble GPS receivers (3 x antenna cables connected to an antenna splitter) all with the same version of firmware, 1 x Zephyr Antenna, 3 x TSC1 controllers/data loggers (one each for VRS-RTK and Classic-RTK and one for raw data logging for post-processing purposes), all with the same version of software, 1 x VRS-GSM module with cable (for roving VRS-RTK), and 1 x RTK Radio and Whip Antenna (for roving Classic-RTK technique)
Both real-time and raw GPS data were collected at each of the selected points. The data then allowed results to be compiled for the following GPS techniques: • Classic-PP (Post Processed), • VRS-PP (Post Processed), • Classic-RTK, and • VRS-RTK Classic-PP observations and processing At each test site one of the GPS receivers logged raw data throughout the station occupation. These data, logged at five second intervals, were used for both Classic-PP and VRS-PP. Since it was expected that the coordinates derived from the Classic-PP technique would be very similar to NRM&E published coordinates, and not all stations had known NRM&E published coordinates, results from this technique were ultimately adopted as truth (or known positions) against which all other results were compared. This is similar to the procedure adopted by (Higgins and Talbot, 2001) where two thirds of the stations were observed with fast static to create some true values for comparison with the VRS results. The raw GPS data logged from the four VRS reference stations were managed by the VRS Rinex Generator Utility software. This software facilitates the downloading of the Rinex data of the VRS reference stations at specified virtual reference positions, as well as at physical reference stations, for post-processing purposes. For these tests, all Rinex files were produced at a five second logging rate to correspond to the logging rate of the GPS rover unit. GPS baseline and network adjustments were carried out using the Trimble Geomatics Office (TGO) software. Depending on the geographic location of the point surveyed, the Rinex files for the three closest VRS reference stations were used for post-processing. GPS baselines to each VRS reference station were processed and used in a network adjustment to calculate the coordinates of the rover station. All baselines were processed using data above a 20 degree elevation mask to remove any noisy data low to the horizon in the urban environment. A fully constrained adjustment was carried out, holding the published coordinates of each VRS reference station fixed. In this way a single point coordinate, with statistics indicating its resultant quality, were attained for each test point. VRS-PP observations and processing Within the VRS software is a function called Virtual Rinex Generator. This function allows the postprocessing of raw GPS data in much the same way as the VRS-RTK technique, except that it is carried out in the post-processing mode rather than in real time. Users are required to provide approximate geographic coordinates (in the WGS 84 datum) of the static roving receiver and the software then generates a synthesized Rinex file based on a position that is very close to the rover receiver. The VRS-PP processing method mirrors that of the Classic-PP method. The only difference being, instead of using three corresponding Rinex files for the VRS reference stations, only a single virtual Rinex file was required. This Rinex file was then post-processed after combining with the static receiver file. Resultant baseline lengths were then only metres long because the virtual base station is very close to the static receiver. In this case, only a single GPS baseline was calculated between the virtual base station and the roving receiver. The adjustment method and baseline acceptance criteria were identical to those used for the Classic-PP method.
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RTK observations and processing The Classic-RTK base station was set on points with known (published by NRM&E) coordinates, which were, like the VRS reference stations, assumed to be error free for the purpose of this research. The base stations were Trimble 4700 receivers with micro-centred L1/L2 antenna. As seen in Figure 2 on the left, three GPS receivers were connected to an antenna splitter. The antenna splitter splits the GPS signals from the Zephyr GPS antenna to the three GPS receivers simultaneously. This is done to enable all three GPS receivers to receive the same GPS signals, subjected to similar site conditions, at the same time. One receiver was used to log raw GPS data for later post processing while simultaneously the remaining two receivers were used to collect Classic-RTK and VRS-RTK data.
Figure 2. Typical test site set-up
The set-up for VRS-RTK is similar to Classic-RTK except that, rather than using VHF or UHF radios, communications to the VRS central network processor is via a GSM data module accessing the GSM phone network. It should be noted however that, although the rover receivers are receiving the same GPS signal, and the same survey style configuration was selected for both Classic-RTK and VRS-RTK observations, the Classic-RTK base station is not directly comparable to the VRS-RTK virtual base station. For example, site specific influences, such as multipath, may be present at the Classic-RTK base station and not at the VRS stations, and visa versa. Consequently, some caution needs to be exercised when comparing Classic-RTK and VRS-RTK results quoted in this paper. On the other hand, this demonstrates one of the benefits of VRS-RTK over Classic-RTK: the VRS-RTK reference stations are located where they will be less susceptible to such site specific influences. To minimise the time bias factor, each of the data collectors (TSC1) used to log Classic-RTK and VRSRTK were simultaneously triggered to start initialisations. For each of the RTK techniques, each set of individual measurements comprised three epochs of measurements taken immediately after an initialisation fix. Between 35 and 50 measurements were taken at each test site for each of the RTK techniques. At the same time, Fast Static GPS data were logged at five second intervals, for a minimum of 30 minutes, to be used for later processing via the VRS-PP and Classic-PP techniques. For the initialisation assessment, comparisons were made between on-the-fly (OTF) initialisation times using the VRS-RTK against the Classic-RTK technique. After each set of individual measurements was
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completed, the receivers were forced to lose lock on the satellites and a re-initialisation was carried out. This loss of lock was achieved by either covering the GPS antenna or using the survey controller reinitialisation function. After loss of lock, the re-initialisation occurred automatically (without user intervention) because the system was configured to carry out OTF initialisation by default whenever it acquired satellite lock. The initialisation time or time to first fix (TTFF) was calculated for each initialisation at each site. Every action or command initiated in the TSC1 controller is automatically time stamped. The data recorder file was opened in a spreadsheet and, for every individual initialisation, the time of initialisation gain was subtracted from the preceding time of initialisation loss and subsequent satellite signal reacquisition to determine the TTFF. For accuracy analysis, known or ground truth positions were taken to be Classic-PP. The coordinates of each point measured were compared against the Classic-PP coordinates by calculating residuals between observed and known positions from Classic-PP. These residuals were expressed as a horizontal twodimensional vector (without sign), and a one-dimensional vertical vector (with sign). This provided an opportunity to assess and compare the Classic-RTK and VRS-RTK in terms of both accuracy and precision.
RESULTS ANALYSIS AND DISCUSSION Post Processed Accuracy Both the Classic-PP technique, after a fully constrained adjustment, and VRS-PP technique yielded point coordinates for each of the test sites. In the case of the Classic-PP adjustment the TGO software estimated the precision of the final adjusted coordinates (although each point has slightly different statistics) to be in the order of 12mm to 13mm for both Easting and Northing and 32mm for height at the 95 percent confidence level. Classic-PP coordinates were adopted as known or ground truth positions to be used as a standard of comparison because: • the network statistics (after scaling for variance factor) appeared to be reliable, • it was expected that the Classic-PP might be more reliable than the VRS-PP due to the single baseline of the latter, • known or published coordinates were only available for 10 of the 15 test sites, • the existing network may contain some bias making the published coordinates less suitable as a standard of comparison, and • this technique is similar to that used by others for similar studies in the past (Higgins & Talbot 2001). For each station, the coordinates of the fully constrained Classic-PP adjustment were subtracted from: • the published coordinate values (only known for 10 of the 15 test stations), and • the VRS-PP coordinate values. Figures 3(a), (b) and (c) show the results of this comparison. In these figures, the horizontal axis represents the ground stations and the vertical axis depicts the residuals against Classic-PP coordinates. The duration of the observation sessions varied between 30 and 45 minutes.
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(a) Easting value of published coordinates and VRS-PP compared to Classic-PP
(b) Northing value of published coordinates and VRS-PP compared to Classic-PP
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(c) Height value of published coordinates and VRS-PP compared to Classic-PP Figure 3. Comparison of published coordinates and VRS-PP compared to Classic-PP As can be seen from Figures 3(a) and (b), the Classic-PP and VRS-PP agree reasonably well in the horizontal except for point P115759 in the northing component, which shows a residual of 31 mm. The mean difference in coordinates between the Classic-PP and VRS-PP for all observations at the fifteen stations was +6 mm in easting, +1 mm in northing and +1 mm in height. The mean difference in coordinates between the Classic-PP and published coordinates for all observations at the ten stations for which published coordinates were available was 0 mm, -9 mm and -4 mm in easing, northing and height, respectively. A small bias was noticed in the northing component when comparing the published values against the Classic-PP. This may indicate a small anomaly in the existing published coordinates, although the residuals are so small that it is difficult to make any definitive statement in this regard. For Classic-PP, it is recommended that for a short baseline of less than 20 km and a minimum of six satellites in view, the minimum occupation time would be eight minutes and about 20 minutes with data from four satellites (Trimble, 2001). Therefore, it is assumed that a typical VRS-PP survey style would require between eight to 12 minutes of data. However, further research is recommended to validate this statement. In any case, the fast occupation time using the VRS-PP technique would be useful for control positioning work, provided sufficient redundancy is built into the network of control being coordinated. RTK 2D accuracy The coordinates, of each point measured, were compared against the Classic-PP to obtain an indication of the accuracy of the Classic-RTK and VRS-RTK techniques. In this section, plots from Classic-RTK and VRS-RTK correspond with respect to their X-axis. The bars are aligned vertically to represent the same ground point. To facilitate easy comparisons, these points are also presented in the same order as graphs in Figures 3(a), (b) and (c). Data for Classic-RTK and VRS-RTK have not been shown on the same graph because they are using different base stations. In the case of Classic-RTK, the labels along the horizontal axis represents the distance the rover receiver (at the test site) is away from the base station. In the case of VRS-RTK the labels along the horizontal axis relate to the proximity of the rover test site to the VRS network; being either inside (In), on the boundary (Bdy), or outside the network offset some distance orthogonally from the triangle boundary formed by straight lines between the VRS reference stations (x km). Figure 4 shows a two-dimensional horizontal comparison between Classic-RTK and VRS-RTK techniques.
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Figure 4. Two dimensional accuracy of VRS-RTK compares favourably with Classic-RTK
The vertical axis of Figure 4 represents a radial distance of the RTK coordinates from the Classic-PP 2
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coordinates. This distance is defined as ΔE + ΔN where ΔE and ΔN are the RTK horizontal point coordinates minus the Classic-PP point coordinates in easting and northing, respectively. Figure 3 demonstrates that the Classic-RTK radio lost communication with the base (NRC) for all marks over 12.7 km from the base station (note that the manufacturers do not recommend use beyond 10 km). Consequently, only nine stations were coordinated by the Classic-RTK technique. At the other six stations, Classic-RTK coordinates were not obtained due to the restriction of limited radio range and communications. At all fifteen sites, it was possible to gain initialisations using VRS-RTK regardless of where they were within (or indeed outside) the network area. This clearly highlights one of the advantages of VRS-RTK over Classic-RTK. To coordinate these other six stations using Classic-RTK the observer would have to re-establish the conventional base station closer to the rover site, which demonstrates that in these situations VRS-RTK has a time advantage over Classic-RTK. The manufacturers of the GPS receivers used in the tests, quote horizontal accuracy of 1 cm + 1 ppm of the baseline length at the 1σ confidence level (Trimble, 2001). As the distance from the base station increases, in general, a degradation of accuracy would have been expected for Classic-RTK. This is not clearly discernable from the above data, probably because this trend is masked by other factors such as different site characteristics and the change in time and satellite configuration between observation sets. The accuracy of the VRS-RTK seems to be reasonably consistent throughout, even for stations outside the network. This is consistent with findings of Santala and Totterstrom (2002) who found that the distance from the rover to reference stations does not weaken the accuracy.
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With respect to the VRS-RTK technique, the differences were reasonably consistent, with most differences (13 points) well within 20mm. The largest difference for VRS-RTK was 26 mm. All except two points for the Classic-RTK were within 20mm; the notable exception was the point located 9.5 km from the base station, which recorded a 36 mm difference. The average of all observations was 14 mm for the Classic-RTK mode and 13 mm for VRS-RTK. In general, the results of Classic-RTK demonstrate a somewhat similar pattern to the VRS-RTK. The results for the point located at the 0.75 km mark (P71400) are of limited use. Due to very high multipath (or some other) effects at the Classic-RTK base station, initialisations in the Classic-RTK mode took an average of 456 seconds. Consequently, only five Classic-RTK initialisations were recorded over the duration of the occupation. In comparison, the average time to gain initialisation for the VRS-RTK at the same point was 38 seconds, and 43 initialisations were gained (which demonstrates the robustness and reliability of VRS-RTK). This point is included in subsequent graphs but should be treated with caution due to this small number of initialisations in the Classic-RTK mode. In all other cases, the results reflect the mean of between 35 and 50 readings. RTK height accuracy Figure 5 shows a height comparison between Classic-RTK and VRS-RTK techniques. The vertical axis reflects the residuals of the height components of each measurement against those derived from ClassicPP.
Figure 5. Height accuracy of VRS-RTK compares favourably with Classic-RTK
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The manufacturer specifications for the height component is 20mm + 2ppm of the baseline length (Trimble 2001). The results from the Classic-RTK vary from +56 mm to -60 mm. Attention is drawn to the 1.1 km mark for Classic-RTK (residual -60 mm). The point of interest (P120956) is located at the edge of a footpath, with a tree on one side and a lamp-post just two metres away. This location may have been subjected to multi-path, and during the data collection process the TSC1 alerted the user of high RMS values. However, good agreement was recorded between the ClassicPP and the VRS-RTK modes. With respect to the VRS-RTK technique, the differences were reasonably consistent with most differences (14 points) well within ±30mm. The only point greater than this was the point 10.5 km outside the network, which recorded a difference of +51 mm. These results suggest that the VRS system performs better than Classic-RTK for the height component. This was expected due to the superior atmospheric and ionospheric modelling of VRS: VRS-RTK interpolates between surrounding reference stations for this modelling, whereas Classic-RTK requires extrapolation from the base station to the rover site. It is also worth noting that differences between Classic-RTK and VRS-RTK could at least partly be due to site-specific interference such as multipath at the Classic-RTK base station. RTK precision (and combined accuracy) All RTK observations were pooled (by combining their residuals against Classic-PP) to provide an indication of the spread of the observations, or the repeatability of each RTK mode. It is recognised that combining all observations in this way may not be statistically sound for various reasons, for example, different precisions are expected from different base station sites. However, the results are considered informative because they provide an empirical estimate, from the data collected during these tests, of the precision that could be expected under normal field conditions. Figure 6 depicts the mean difference and the 95 percent confidence interval of all observations for the horizontal and height components of both RTK modes.
Figure 6. Precision of VRS-RTK compares favourably with Classic-RTK The combined sample size of measurements taken for the Classic-RTK mode was 300, and 595 for the VRS-RTK mode. The difference in total observations is due to the reduced number of Classic-RTK observations, at the 0.75 km mark (P71400) and the stations where radio communications were not possible. Although accuracy was considered in the previous section, the graphs in Figure 6 provide further information on the pooled data. The mean horizontal accuracy for the Classic-RTK mode was 14 mm, and 13 mm for VRS-RTK. Precision for the Classic-RTK mode was ±30 mm at 2σ (95 percent). For the VRS-RTK mode the precision was estimated to be ±20 mm at 2σ (95 percent). Although this increased
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precision for VRS-RTK is not large, it may well be attributed to the added redundancy provided by the multiple reference stations as noted in previous research (Higgins and Talbot, 2001). For the height component, the VRS-RTK mode averaged +5 mm with a precision of ±56 mm at 2σ (95 percent) while the Classic-RTK mode averaged -12 mm with a precision of ±75 mm at 2σ (95 percent). These results are somewhat better than results from earlier testing of the VRS-RTK (Higgins, 2002; Higgins, 2001), which produced an expected horizontal accuracy for the VRS-RTK of 32 mm. The horizontal precision was estimated to be ±14 mm at the 1σ confidence level, which equates to 27 mm at 95 percent confidence. The absolute vertical accuracy was calculated as 40mm with a precision of ±31 mm, which equates to ±60 mm at 95 percent confidence. These results also compare favourably to results achieved from recent testing of the SIM-RSN. Test results revealed that VRS-RTK positioning, using similar equipment, can be achieved to within 30mm accuracy in horizontal position and 10mm to 50mm vertical (Hu et al. 2003). Time to first fix (TTFF) It is recognised that many variables can affect initialisation times including: number of satellites, satellite geometry, ionospheric interference, multipath, radio interference, and signal strength. The same number of satellites and satellite geometry were experienced by both of the RTK modes because GPS data were received from the same antenna and the same elevation mask was set in each data collector. However, care still needs to be exercised in comparing different sites, as the satellite geometry will vary from site to site, and in comparing between RTK modes, as the base stations are in different locations and will be experiencing different site specific interference. The initialisation times at nine different sites for ClassicRTK (300 initialisations) and fifteen different sites for VRS-RTK (595 initialisations) were averaged and plotted against time. The results are shown in Figure 7.
Figure 7. TTFF of VRS-RTK compares favourably with Classic-RTK To keep the vertical axis of the graph at a readable scale, due to the disproportionately high initialisation times (456 seconds on average) experienced at the 0.75 km mark (P71400) in the Classic-RTK mode, data from this point have been omitted. In comparison at the same point, the VRS-RTK took an average of 38 seconds for initialisation.
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The data from the 0.75 km mark (P71400) in the Classic-RTK mode have also been omitted from the calculated TTFF statistics. The rejection of outliers (any observations greater than 3σ from the mean) is a well accepted practice, which was used in the early testing of the VRS, and was justified by the fact that it is consistent with best practice guidelines (Higgins and Talbot, 2001). The plots shown in Figure 7 illustrate good correlation (0.74 correlation coefficient) between the TTFF for each RTK technique. The initialisation times for both the Classic-RTK and VRS-RTK techniques were typically less than 60 seconds. It exceeded 60 seconds at only one point. This set-up was only a few metres away from an intersection of a collector road with a sub-arterial road, and measurements were taken during evening peak hour traffic. At this site, a number of large container trucks were negotiating turns from the collector road to the sub-arterial road. This raises the possibility of loss of satellite lock or multipath contributing to the longer initialisation times (for both Classis-RTK and VRS-RTK) at this point. The average TTFF for all observations were 40 seconds for Classic-RTK and 32 seconds for VRS-RTK. For Classic-RTK, 50 percent of all initialisations were within 23 seconds and 95 percent were within 112 seconds. For VRS-RTK, 50 percent of all initialisations were within 22 seconds and 95 percent were within 77 seconds. These initialisation times are somewhat smaller compared to results of earlier testing of the VRS pilot project where the average initialisation time was 2 minutes, but this varied with the number of satellites being tracked (Higgins, 2002; Higgins, 2001). Higgins later found that 50 percent of all initialisations during a project for Ipswich City Council were within 50 seconds and 95 percent were within 130 seconds (Higgins, 2002; Higgins, 2001). These improvements in initialisation times, and precisions mentioned earlier, were expected due partly to the following improvements (Higgins and Talbot, 2001): • Updates to the VRS software that have improved modelling, • Use of precise ephemeris (during initial pilot testing VRS only used broadcast ephemerides), and • Improvements in the relative VRS reference station coordinates. Results from this testing show initialisation times also significantly faster than those achieved from recent testing of SIM-RSN, which revealed an average initialisation time within 2 minutes (Hu et al., 2003). However, results obtained are similar to those obtained by Santala and Totterstrom (2002) who recorded 90 percent of initialisations in less than 60 seconds. Although giving some indication of general initialisation times, pooling all observations to provide an average value in this manner may be potentially misleading because the site characteristics, satellite configuration and other factors were not the same for each point. Furthermore, the Classic-RTK and VRS-RTK data sets were not identical due to the data being collected at some points with VRS-RTK and not with Classic-RTK. It has been identified that the number of satellites is an important factor when assessing the initialisation times (Hu et al., 2003; Edwards et al., 1999). To confirm this, the initialisation times were grouped with respect to the number of satellites visible at the time of initialisation. Results are shown in Figure 8.
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Figure 8. With few satellites, initialisation time of VRS-RTK was faster than Classic-RTK This graph indicates that during this testing, when operating with a low number of satellites, the VRSRTK initialisation times were faster than the Classic-RTK method. This can be explained by the fact that VRS has superior atmospheric and ionospheric modelling due to this modelling being based on surrounding stations rather than relying on extrapolation from a single base station as is the case with Classic-RTK. Again, it is difficult to draw general conclusions due to the slightly different data sets. Coverage Results from tests carried out show that by using the GSM mobile network for data transmission with VRS-RTK, the constraints of being within 10 km of a base station, and within stable radio communications range are negated. It is only necessary for the VRS is to be within a GSM mobile coverage area. The algorithm and techniques employed by the VRS system to model the errors inflicted by atmospheric effects, and the process of providing a synthesized base station to the roving receiver at the remote end, seems to provide reliable results even beyond the recommended network coverage as advised by the manufacturer. Further testing outside the network area is recommended to validate this hypothesis.
CONCLUSION From the results presented in this paper, it is evident that the VRS system, when used for post-processing, produced final coordinates that were comparable to conventional post-processing from three known stations. It is important to note however that, if the VRS system is to be used for post processing, it is critical to build sufficient redundancy into the network since the VRS post processing from three control stations is essentially reduced to one single short baseline from the virtual reference station. Further research is recommended on the impact this has on accuracy, precision, network planning and resources. Results from 300 observations at nine different stations using Classic-RTK technique, and 595 observations at 15 different stations using VRS-RTK technique, suggest that the VRS System, employing the VRS-RTK technique of positioning, seems at least comparable to, and in some respects may be superior to, the Classic-RTK technique. Although each RTK technique used the same GPS signal from the same GPS antenna, the results quoted must be used with caution. It must be remembered when comparing these results that each RTK technique used different base stations, the site characteristics were not the same for all points that were combined into the overall statistics, and the Classic-RTK and VRS-RTK data sets were not identical due
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to the data being collected at some points with VRS-RTK and not with Classic-RTK. On the other hand, the fact that VRS is less susceptible to radio and base station problems demonstrates that VRS-RTK is more reliable and robust than Classic-RTK. The area over which reliable results were obtained for the VRS-RTK technique were better than expected with no discernable reduction in quality for observations taken up to 10.5 km outside the VRS network. These tests also highlighted some major advantages of VRS-RTK over the conventional RTK method: no base station had to be set, monitored and secured, and observations were not limited by distance from the base station or radio communications. During these tests, the VRS-RTK proved to be a capable replacement for conventional RTK. This finding is consistent with previous research (for example Santala and Totterstrom, 2002), which suggests that VRS can significantly improve both productivity and measurement quality.
ACKNOWLEDGEMENTS The authors wish to acknowledge the support of the staff and management of the Department of Natural Resources Mines and Energy, Queensland. In particular, the assistance from Garry Cislowski with the field data capture was critical to the achievement of the project’s objectives. Acknowledgement is also due to Matt Higgins and Kevin McDougall for their advice on the writing of this paper and their valuable contributions with proof reading and editing.
REFERENCES Brockmann, E., Grunig, S., Hug, R., Schneider, D., Wiget, A., Wild, U. (2001) Introduction and first application of Real-Time Precise Positioning Service using the Swiss Permanent Network AGNES, Swiss Federal Office of Topography, National Report of Switzerland. Edwards, S.J., Cross, P.A., Barnes, J.B. and Betaille, D. (1999) A methodology for benchmarking realtime kinematic GPS, Survey Review, vol. 35, pp. 163-174. Higgins, M.B. (2001) The Changing Nature of Surveying Infrastructure from Marks in the Ground to Virtual reference Stations, Paper presented to A Spatial Odessey: 42nd Australian Surveyors Congress, Brisbane, Australia, 25-28 September. Higgins, M.B. (2002) Australia's Changing Surveying Infrastructure from Marks in the Ground to Virtual Reference Stations, Paper presented to FIG XXII International Congress, Washington, D.C. USA, 19-26 April. Higgins, M.B. and Talbot, N. (2001) Centimetres for Everyone: Initial Results from an Australian Virtual Reference Station Network Pilot Project, Paper presented to SatNav 2001, The 5th International Symposium on Satellite Navigation Technology and Applications, Canberra, Australia, 24-27 July. Hu, G.R., Khoo, H.S., Goh, P.C. and Law, C.L. (2003) Development and assessment of GPS virtual reference stations for RTK positioning, Journal of Geodesy, vol. 77, no. 5/6, pp. 292-302. Lachapelle, G., Alves, P., Fortes, L.P., Cannon, M.E and Townsend, B. (2000) DGPS RTK positioning using a reference network, Paper presented to 13th International Technical Meeting Satellite Division US Instrument Navigation, Salt Lake City, UT, 19-22 September. Retscher, G. (2002) Accuracy Performance of Virtual Reference Station (VRS) Networks, Journal of Global Positioning Systems, vol. 1, no. 1, pp. 40-47. Santala, J. and Totterstrom, S. (2002) On Testing of RTK-Network Virtual Concept, Paper presented to FIG XXII International Congress, Washington, D.C. USA, 19-26 April. Trimble (2001) 5700 GPS User Guide, vol. Version 1.00, Revision A, January, Trimble Navigation Limited, Sunnyvale, CA.
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