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GPS SINGLE POINT POSITIONING WITH SA OFF: HOW ACCURATE CAN WE GET? Chalermchon Satirapod, Chris Rizos and Jinling Wang School of Geomatic Engineering The University of New South Wales Sydney, NSW 2052 Australia

ABSTRACT The announcement by U.S. President Bill Clinton to turn off 'Selective Availability' at midnight (Washington DC time) 1 May 2000 caught everyone by surprise. This decision to stop degrading the accuracy of the Global Positioning System's (GPS) Standard Positioning Service (SPS) will have a significant impact on users all over the world. One important outcome for the geomatics community is that the substantial improvement to GPS Single Point Positioning (SPP) results could make it an attractive alternative to the Differential GPS (DGPS) mode of positioning. In this paper some results from different SPP processing strategies are presented, and the accuracy improvement in the case of averaged static solutions is discussed. Finally, the paper speculates on the attainable SPP accuracy using single-frequency GPS receivers when the ionospheric activity is less intense in the future.

INTRODUCTION In the past, the instantaneous accuracy of GPS Single Point Positioning (SPP) was limited by many errors, including satellite ephemeris error, satellite clock bias, atmospheric effects, receiver noise and multipath. In addition, Selective Availability (SA) has been the dominant source of error for SPP since its introduction on 25 March 1990. As a result the instantaneous accuracy of SPP degraded to about 100 metres in the horizontal components, and approximately 156 metres in the vertical component (at the 95% confidence level). However, the decision by U.S. President Bill Clinton's administration to 'turn off' SA on 1 May 2000 [1], is expected to have a significant impact on a wide range of users worldwide. One potential important outcome for the geomatics community is that the substantial improvement to GPS SPP results could make it an attractive alternative to the Differential GPS (DGPS) mode of positioning for some applications. The improvement in instantaneous accuracy of GPS SPP is clearly seen for the period immediately before and after SA was 'switched off', for a static GPS receiver on the 2nd May 2000, in Figure 1. The first three subplots are the discrepancies in the three coordinate components relative to the known coordinates, and the bottom subplot displays the number of satellites that were observed. In the investigations reported here, Precise Single Point Positioning (PSPP) software developed at the University of New South Wales (UNSW) was used to derive the GPS SPP solutions. This software allows input of the precise International GPS Service (IGS) orbits and corresponding satellite clock corrections. These are of higher quality than the information available from the navigation message, hence the impact of residual satellite ephemeris and satellite clock errors (after using the broadcast ephemerides and satellite clock error model) can be studied. Furthermore, the ionosphere-free linear data combinations can be used to derive SPP solutions, permitting the impact of the unmodelled (or mismodelled) ionospheric measurement delay to be investigated. Some results from different SPP processing strategies are presented in this paper, and the accuracy improvement gained from averaged static

solutions (as opposed to instantaneous, or single epoch, solutions) is discussed. Finally, the paper speculates on the attainable SPP accuracy using single-frequency GPS receivers when the ionospheric activity is less intense in the future, when the sunspot count associated with the 11 year solar cycle is not a maximum.

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Fig 1 The instantaneous accuracy results of GPS Single Point Positioning (2nd May 2000), before and after Selective Availability was 'switched off'.

EXPERIMENTS Data Collection One experiment was carried out on the roof of the Geography and Surveying (GAS) building, at UNSW, Sydney, Australia, using data collected by a Leica CRS1000 GPS receiver connected to an Ashtech antenna. The data was collected in static mode between the 16th and 22nd May 2000 at a 15-second rate. The photograph in Figure 2 shows the GPS receiver set up on the Mather Pillar station on the roof of GAS building. Establishment of Reference Coordinates In order to obtain accurate coordinates in the International Terrestrial Reference System, the University of Bern precise GPS data processing software, referred to simply as the 'Bernese version 4.0', was used to compute the coordinates of the Mather Pillar. The data from the TIDB station, one of the IGS permanent stations located near Canberra, was downloaded via the Internet. From previous data collected at the Mather Pillar in 1998 and the TIDB station, the coordinates of the Mather Pillar were computed using the Bernese software. These coordinates are consistent with the reference frame ITRF97 to within a few centimetres. Considering that the broadcast ephemerides and precise IGS orbits used in the PSPP software are given in the WGS84 and ITRF97 coordinate reference systems respectively, the solutions would subsequently refer to the WGS84 and ITRF97 coordinate systems. According to [3],

the WGS84 reference frame is coincident with ITRF97 at a level better than 2 cm, and therefore the difference between WGS84 and ITRF97 can be considered as being insignificant in the context of this study.

Fig 2 The Mather Pillar station at GAS, UNSW.

Data Processing Strategies The data processing involved using the Precise Single Point Positioning (PSPP) software developed at UNSW. The details of this software can be found in [6]. The data was processed in turn using the precise IGS orbits and the broadcast ephemerides. The Saastamoinen model was chosen as the standard troposphere model for all the data processing runs. Two ionospheric delay processing strategies were used. The first was based on using the broadcast ionosphere model, while the second strategy used the ionosphere-free linear data combination of the L1 and L2 pseudo-range observations. For further details on these models see [2]. ANALYSIS OF RESULTS Analysis of Results--Static Mode The data was processed in single 24-hr observation files, hence a considerable amount of 'averaging' occurs. Seven solutions were obtained for each data processing run. Single-frequency data The single-frequency data from the Leica CRS1000 GPS receiver was first processed with the broadcast ionosphere model and the broadcast ephemeris. The broadcast ionosphere model and the precise IGS orbit were then applied to the same data set. The day-to-day discrepancies in the three coordinate components compared to the known coordinates are plotted in Figures 3 and 4. (Figure 3 shows the day-to-day mean discrepancy and RMS values derived using the broadcast ephemeris, the Saastamoinen troposphere model and the broadcast ionosphere model.)

Fig 3 SPP day-to-day mean discrepancy and RMS values (broadcast ephemeris, Saastamoinen troposphere model and broadcast ionosphere model) Top: Day-to-day mean discrepancies. Bottom: Day-to-day RMS values

Figure 4 shows the day-to-day mean discrepancy and RMS values derived using the precise IGS orbit, the Saastamoinen troposphere model and the broadcast ionosphere model.

Fig 4 SPP day-to-day mean discrepancy and RMS values (precise IGS orbit, Saastamoinen troposphere model and broadcast ionosphere model) Top: Day-to-day mean discrepancies. Bottom: Day-to-day RMS values

Dual-frequency data The strategy of using dual-frequency observations to form the ionosphere-free linear data combination was then used to effectively eliminate the ionospheric bias. This data was then first processed with the broadcast ephemeris, and then with the precise IGS

orbit. The day-to-day discrepancies in the three coordinate components, when compared with the known coordinates, are plotted in Figures 5 and 6. (Figure 5 shows the day-to-day mean discrepancy and RMS values for the three coordinate components, derived using the broadcast ephemeris, the Saastamoinen troposphere model and the ionosphere-free data model.)

Fig 5 SPP day-to-day mean discrepancy and RMS values (broadcast ephemeris, Saastamoinen troposphere model and ionosphere-free model) Top: Day-to-day mean discrepancies. Bottom: Day-to-day RMS values

Figure 6 shows the day-to-day mean discrepancy and RMS values derived from using the precise IGS orbit, the Saastamoinen troposphere model and the ionosphere-free data model.

Fig 6 SPP day-by-day mean discrepancy and RMS values (precise IGS orbits, Saastamoinen troposphere model and ionosphere-free model) Top: Day-to-day mean discrepancies. Bottom: Day-to-day RMS values

With reference to Figures 3-6, the following concluding remarks can be made: • The day-to-day mean values in Figures 5 and 6 are more regular than those in Figures 3 and 4. This is mainly due to the residual ionosphere bias remaining after using the broadcast ionosphere model. • The use of the precise IGS orbit and satellite clock corrections, with the broadcast ionosphere model, can reduce the orbit biases, resulting in more consistent results in terms of both the mean discrepancy and RMS values. • In terms of the mean discrepancy between derived SPP coordinates and the known ITRF97 coordinates, use of the ionosphere-free model with the precise IGS orbit and satellite clock corrections, delivered the highest accuracy solutions. The accuracy of SPP solutions is less than 1 metre in all the components over the 24-hr observation period. • According to an IPS report [4], an ionosphere disturbance occurred in the southern region of Australia between the 16th and 17th May 2000. This disturbance, however, does not appear to have had any significant impact on the SPP results. • The results of single-frequency data analysis demonstrate that an accuracy of 1 to 1.5 metres in the horizontal components, and 2 to 4 metres in the vertical component, could be achieved over a 24-hr observation period. Analysis of Results--Kinematic Mode In the previous section, the results from the SPP experiment were analysed in the static mode. Epoch-by-epoch SPP solutions are also interesting to analyse. This is equivalent to considering the experiment as being run in the kinematic mode, continuously for a period of 7 days. In the following analyses, the point positioning performance is characterised by the Distance Root Mean Square error. Typical probability values for 1.DRMS and 2.DRMS are 68.27% and 95.45% respectively [5]. The results from the analyses are summarised in Table 1. Table 1. Single-epoch SPP coordinate accuracy, at 2.DRMS

Single-frequency data (broadcast ephemeris) Single-frequency data (precise IGS orbits) Dual-frequency data (broadcast ephemeris) Dual-frequency data (precise IGS orbits)

Horizontal accuracy (m) 6.83 4.24 5.19 3.22

Vertical accuracy (m) 12.30 8.07 9.68 4.93

In relation to Table 1, the following comments can be made: • Based on the results obtained from these analyses, the use of dual-frequency data can improve the accuracy of solutions for both the horizontal and vertical components. The accuracy improvements in horizontal and vertical components are approximately 25% and 20-40%, respectively. • Previous analyses of GPS SPP solutions using post-mission information can be found in [7]. According to [7], the accuracy of SPP solutions for the horizontal component using single-frequency data is approximately the same as the results obtained from this study. However, the degradation of accuracy in the vertical component becomes more pronounced in the current data set because the ionosphere is more active this year.

• It is clear that the use of precise IGS orbit and satellite clock correction information produces higher accuracy solutions. From processing the same data set with the satellite coordinates obtained from the precise IGS orbits and the satellite clock corrections from the broadcast ephemeris, it can be concluded that there is no improvement in accuracy compared to the use of the broadcast ephemeris. The only significant difference between the precise IGS data and the broadcast ephemeris at the metre accuracy level is the satellite clock correction information. Accuracy Improvement--Averaged Static Solutions The solutions were averaged using various window lengths ranging from 5 to 60 minutes with a total observation period of 7 days. The positioning performance for each window length was computed at 2.DRMS (95% confidence level). The results from analyses of single-frequency as well as dual-frequency data are presented in Table 2, where the first column shows the data used, the second column shows the window length, the third column shows the horizontal accuracy as well as the accuracy improvement in percentage (compared to the single-epoch accuracy), and the fourth column shows the vertical accuracy and the accuracy improvement. Table 2. Averaged static solution accuracy, at 2.DRMS and an acccuracy improvement in percentage Data Single-frequency

Dual-frequency

Window length (min) 5 10 15 20 30 60 5 10 15 20 30 60

Horizontal accuracy (m) and improvement(%) 6.79 (0.6%) 6.74 (1.3%) 6.70 (1.9%) 6.65 (2.6%) 6.57 (3.8%) 6.31 (7.6%) 5.12 (1.4%) 5.05 (2.7%) 4.99 (3.9%) 4.92 (5.2%) 4.81 (7.3%) 4.42 (14.8%)

Vertical accuracy (m) and improvement(%) 12.19 (0.9%) 12.06 (2.0%) 11.99 (2.5%) 11.88 (3.4%) 11.63 (5.5%) 11.10 (9.8%) 9.47 (2.2%) 9.27 (4.2%) 9.13 (5.7%) 8.99 (7.1%) 8.70 (10.1%) 7.98 (17.6%)

From Table 2, the following comments can be made: • Averaged static solutions of single-frequency data do not show any significant improvement in accuracy, even though up to a 60-min window length was used. • On the other hand, the averaged static solutions of dual-frequency data show more improvement in accuracy. An explanation for this could be that the use of the ionosphere-free linear combination model increases the measurement noise by approximately three times that of the original L1 observation [5]. As a result, averaging the static solutions would average out the measurement noise, resulting in improved accuracy.

CONCLUSIONS The results obtained using the broadcast ephemeris indeed indicate that the removal of SA has dramatically improved the instantaneous accuracy of GPS SPP solutions. In the static point positioning analyses, the use of dual-frequency data with the precise IGS orbit produced solutions that were found to be consistent with the known coordinates at the 1 metre level in all the components, while the use of singlefrequency data with the precise IGS orbit show that an accuracy of 1 to 1.5 metres in the horizontal components and 2 to 4 metres in the vertical component could be achieved using long observation sessions (in this case a 24-hr observation period). In the case of single-epoch solutions it is possible to attain an instantaneous accuracy of better than 5.2 metres using dual-frequency data and 6.8 metres using single-frequency data, for the horizontal components (at 95% confidence level). An accuracy of better than 9.7 metres using dual-frequency data and 12.3 metres using single-frequency data was obtained for the vertical component, at the same confidence level. However, in the case of using single-frequency data, higher accuracy for both the horizontal and vertical components can be expected in future when the ionosphere is less active. When using averaged static solutions, higher accuracy can be expected with the use of dual-frequency data. ACKNOWLEDGEMENTS The first author is supported in his Ph.D. studies by a scholarship from the Chulalongkorn University, Thailand. The authors would like to thank Dr. Toshiaki Tsujii for his valuable comments and special thanks to Mr. Liwen Dai for providing the data used in this study. Much gratitude also goes to Mr. Clement Ogaja for his kind assistance in the preparation of this paper. References 1. 2. 3. 4. 5.

6. 7.

Clinton, B., 2000. White house’s web page: http://www.pub.whitehouse.gov/urires/I2R?urn:pdi://oma.eop.gov.us/2000/5/2/8.text.2 ICD-GPS-200C, 2000. Navstar GPS Space Segment/Navigation User Interfaces (Electronic copy) 138pp. IGS, 1999. International GPS service’s web page: http://igscb.jpl.nasa.gov/faqs.html IPS, 2000. Australian Space Forecast Centre’s web page: gopher://gopher.ips.gov.au:70/hh/rwc/reports Rizos, C., 1997. Principles and practice of GPS surveying, Monograph 17, School of Geomatic Engineering, The University of New South Wales, ISBN 0-85839-071-X, 555pp. Satirapod, C., 1998. General report: Precise Single Point Positioning Software, School of Geomatic Engineering, The University of New South Wales, 87pp. Satirapod, C., Rizos, C. and Han, S., 1999. GPS Single Point Positioning: An Attractive Alternative? Proceeding of the 4th International Symposium on Satellite Navigation Technology & Applications, Brisbane, Australia, 20-23 July, paper 47.