Research Facility of GPS Network-Based Real-Time Kinematic Positioning System in ISKANDAR Malaysia

Shariff, N. S. M., Musa, T. A., Omar, K., Khairul, A.A.

UTM-GNSS & Geodynamics Research Group,

Infocomm Research Alliance, Faculty of Geoinformation Science & Engineering,

Universiti Teknologi Malaysia (UTM), 81310 Skudai, Johor, Malaysia.

suryatishariff@gmail.com; tajulariffin@utm.my

ABSTRACT

In equatorial region, severe atmospheric delays occur frequently which leads to difficulties in the ambiguity resolution process and thus affects the accuracy of RTK positioning. The idea of N-RTK system which is to reduce distance-dependent errors, enable high accuracy RTK positioning to be achieved over large area. Hence, the N-RTK system has become popular to be implemented by various agencies and universities. A research-based facility of GPS N-RTK positioning system namely ISKANDARnet has been established by UTM-GNSS and Geodynamics Research Group. ISKANDARnet has been set up with adequately inter-stations distance to assist ambiguity resolution. The data quality of each station is essentially checked by analysing multipath vulnerability. Moreover, generation of real-time network corrections and stability of communication link for inter-stations are monitored to ensure the accessibility of the system. Findings of this study are expected to robust research activities and support the development region of ISKANDAR Malaysia. Keywords: Global Positioning System, Network-based positioning, Multipath, Cycle slip 1. INTRODUCTION Over the last decades, high precision and reliable positioning service based on the Global Positioning System (GPS) has greatly offered by a single-based Real-Time Kinematic (RTK) technique. Typically, centimeter level positioning accuracy in real-time can be achieved at the RTK user site. However, degradation of positioning accuracy results when user practice the RTK technique over medium and long baseline. This circumstance due to distance-dependent errors (i.e. atmospheric delays and orbital errors) that less correlated over longer baselines. One technique proven in mitigating distance-dependent errors is the Network-based RTK (N-RTK). The N-RTK approach allows modeling the errors by combining and interpolating real-time measurements data from multiple reference stations. The “network corrections” then can be generated and disseminate to the network users to improve their position accuracy. This

N-RTK system can be implemented by deploying permanent receiver stations, known as “Continuously Operating Reference Station” (CORS), communication links for data streaming and correction broadcast, and a processing centre (i.e. control centre). Presently, several regional networks are operational around the world in such locations as in the Australian states of Victoria (GPSnet), NSW (CORSnet) and Queensland (SunPOZ), Germany (SAPOS), Denmark (REFDK), Hong Kong (SatRef), Japan (GEONET), Singapore (SiReNT), and MyRTKnet in Malaysia. Nevertheless, there have only been a few independent N-RTK systems developed by universities and receiver manufacturers (e.g. Rizos et al., 2003). Hence, the GNSS and Geodynamics (G&G) Research Group, Faculty of Geoinformation Science and Engineering, Universiti Teknologi Malaysia (UTM) has initiated to develop a research-based N-RTK system. The so-called GPS ISKANDAR network (ISKANDARnet) system has been established in collaboration with Satellite Navigation & Positioning (SNAP) Laboratory of the University of New South Wales. This paper outline the development of the ISKANDARnet that includes designing network coverage, configuration of reference stations and control center as well as communication links for data streaming. The multipath effects at every reference stations have initially been checked by evaluating of multipath values on L1 and L2. Moreover, cycle slips was examined as part of data quality check. For real-time of data streaming, the connection of each reference stations via internet has also been tested. Finally, essential part of N-RTK system in generating network corrections were monitored and discussed. 2. SYSTEM DESIGN CONSIDERATION Normally, researches on establishing of an N-RTK system commence with designing the network area as well as the location of deploying CORS. It would be a major step forward if a real-time, high precision positioning service could be reliable deployed over a large area without significantly increasing the density of reference stations (Zhang et al., 2006). According to Rizos and Han (2003), the typical distance between reference stations is in the range 50-100km, however it depends on the geographic location of the network and the level of ionospheric activity. For instance, in equatorial region, the high ionospheric activity requires inter-receiver distances of less than 40km to ensure successful network ambiguity resolution. Additionally, Willgalis et al. (2002) indicated that such networks usually cover only densely populated areas or an important economic region. This is due to the expensive infrastructure involved. There is also essential step of selecting appropriate CORS location in order to ensure quality of data (e.g. less multipath effects) that enable sufficient performance in N-RTK system. The architecture of an N-RTK system requires at least three CORS. One of the CORS can be treated as the ‘master station’, that is usually selected as the nearest to the roving user receiver (Musa, 2007). The master station is important for a master-to-reference station to fix the network ambiguities. Meanwhile, each CORS responsible to streams observation data continuously to a control centre via an internet link. The control centre will gather data

streams from the CORS, monitoring the data integrity as well as processing network corrections. The network users then may receive the corrections by several efficient methods such as Virtual Reference Stations (VRS), Flächen Korrektur Parameter (FKP), and master-auxiliary corrections (MAX). Insight of the VRS, FKP and MAX concept can be obtained in Landau et al. (2002), Wubbena et al (2001) and Brown et al. (2006) respectively. An overview of the architecture of network-based positioning is given in Figure 1.

Figure 1: The architecture of the network-based GPS positioning. Generally, the research challenge in the establishment of N-RTK involves with designing the appropriate information technology (IT) components, GPS CORS receiver technology, network algorithm, and user configuration (Lim & Rizos, 2008). Moreover, knowledge on server-based processing and communication link gives advantages of rapid research activities. 3. CONFIGURATION OF ISKANDARnet A new main southern economic and development region in Johor, Malaysia namely ISKANDAR significantly requires reliable positioning system in many range of positioning activities. In order to support this development region, ISKANDARnet has been established to adequately cover metro area of ISKANDAR Malaysia. 3.1 ISKANDARnet Site

Three CORS stations; ISKANDARnet1 (ISK1) at Universiti Teknologi Malaysia (UTM), ISKANDARnet2 (ISK2) at Port of Tanjung Pelepas (PTP) and ISKANDARnet3 (ISK3) at Community College of Pasir Gudang, have been deployed within inter-station distance about 24 km and up to 43 km as shown in Figure 2. The length of inter-station has been designed to keep long enough in order to assist network ambiguity resolution.

CORS 1 / 

Master  Network correction 

CORS 3 

CORS 2 

User

Control Centre 

Internet 

Figure 2: ISKANDARnet Coverage Area.

3.2 Control Center and Reference Stations of ISKANDARnet

The control center of ISKANDARnet has been set up at the Faculty of Geoinformation Science and Engineering (FKSG), UTM, in Johor Bahru. A server computer and internet connection were configured to collect all GPS measurements from the ISKANDARnet reference stations. All the three reference stations are equipped with a dual-frequency Trimble 4700 receiver, micro-centred L1/L2 antenna, server computer, internet connection and Uninterrupted Power Supply (UPS). The antenna has been mounted and set up correspondingly to the suitability of place. For instance, ISK1 and ISK3 were mounted on a building. Meanwhile, the ISK2 was set up on the rooftop of a building by using a stable stand. The location of ISK1, ISK2 and ISKA3 are shown in Figures 3 (a), (b), and (c) respectively.

                                      (a) ISK1 (b) ISK2 (c) ISK3 

Figure 3: Reference Stations of ISKANDARnet

3.3 Communication Link

Communications between reference stations and the control centre are provided via the Transmission Control Protocol / Internet Protocol (TCP/IP), which intended for real-time applications. The Networked Transport of RTCM via Internet Protocol (NTRIP) technology is then applied to enable data streaming through TCP/IP. NTRIP is implemented in three system software components: NtripClients, NtripServers and NtripCaster (Dettmering et al., 2006). The NtripServer is used by each of reference station to stream measurements to the NtripCaster. The control centre utilises the NtripCaster to manage the GPS data streams. Meanwhile, the NtripClient is used by user in order to retrieve the measurement data. The entire of ISKANDARnet system can be illustrated in Figure 4.

Figure 4: The configuration of the ISKANDARnet

4.0 DATA QUALITY CHECK Data quality at every GPS reference station is checked in order to verify the condition of reference stations as well as to provide reliable N-RTK result. Data quality is particularly affected by the multipath effect. The analysis can be done by computing the so-called Root Mean Square of multipath on L1 (RMS mp1) and on L2 (RMS mp2). The “Translation, Editing, and Quality Check” (TEQC) program was used to derive the RMS mp1 and RMS mp2 values. In this study, the multipath effect at ISK1, ISK2 and ISK3 stations were analysed by setting 5 degree of satellite elevation cut-off angle. 4.1 Verification of Multipath Effects at Reference Stations The multipath effect at every reference stations was analysed by taking RINEX data from 6 September 2009 - 14 September 2009 (i.e. Day of Year 249 to 257). Figure 5 and 6 shows the RMS of multipath on L1 and L2 for ISK1, ISK 2 and ISK3 stations.

249 250 251 252 253 254 255 256 2570.05

0.1

0.15

0.2

mp1

Day of Year

RM

S m

p1 (

m)

Figure 5: RMS of Multipath Effect on L1

248 249 250 251 252 253 254 255 256 257 2580.1

0.15

0.2

0.25

0.3

mp2

Day of Year

RM

S m

p2 (

m)

ISK1 ISK2 ISK3

Figure 6: RMS of Multipath Effect on L2

Results indicate that ISK2 is the highest affected by multipath which RMS mp1 is 0.20m in average. Meanwhile, ISK1 shows the lowest multipath effect with 0.07m in average. Similar variation of multipath effects can be seen in RMS mp2. ISK 1 and ISK2 have average of RMS mp2 as 0.14m and 0.29 m. According to Bruyninx et al. (2003), 75 percent of the European reference stations in the EUREF Permanent Network (EPN) have RMS mp1 values below 0.57m and RMS mp2 values below 1m. Furthermore, 50 percent of the International GNSS Service (IGS) stations around the world have RMS mp1 under 0.4m, and 75 percent have less than 0.5m. Meanwhile, the RMS mp2 value for 50 percent of the IGS stations are less than 0.6m and 75 percent are less than 0.75m. It seems that the multipath effects at these reference stations are in the acceptable range. 4.2 Verification of Observations at Reference Stations In this study, data quality is also examined by the number of observation per slips. Generally, the TEQC provide information that consist of number of observation, observation per slips, receiver cycle slips, satellite elevation and azimuth angle, receiver clock drift, and receiver signal-to-noise ratios. Table 1 show four indices of GPS data, i.e., expectation number of observation (expt), number of observation (have), percentage of observation (%) and observation per slips (o/slps) of ISK1, ISK2 and ISK3 stations.

Table 1: Summary of Data Quality    DoY  expt  have  %  o/slps     expt  have  %  o/slps     expt  have  %  o/slps 

249  89256  76866  86  76866  89247  76350  86  76350  89176  77052  86  77052 

250  91723  78656  86  78656  91715  77861  85  77861  91656  78823  86  78823 

251  91738  78796  86  78796  91728  74610  81  9326  91665  78711  86  78711 

252  91749  78816  86  78816  91745  80175  87  40088  91683  78894  86  78894 

253  91768  79205  86  79205  91761  80798  88  26933  91695  78835  86  78835 

254  91774  79157  86  79157  91764  79979  87  11426  91706  78757  86  78757 

255  91780  78856  86  78856  91769  79831  87  19958  91721  78783  86  78783 

256  91413  79390  87  79390  91401  80517  88  40259  91381  79597  87  79597 

ISK1

 

257  91454  79771  87  79771 

ISK2

 

91443  80935  89  80935 

ISK3

 

74659  66913  90  66913  

Note that the index ‘o/slps’ is ‘the number of observations’ divided by ‘the number of cycle slips’ (Yeh et al., 2008). There is no threshold for the o/slps number, but if the cycle slips occurs very often, it probably going to cause problems during data processing. Cycle slips occur frequently in the carrier phase observation, and have similar effects on ambiguity (Yeh et al., 2007). Typically, the number of cycle slips is per 1000 observations to facilitate the interpretation of cycle slips at the reference station. Figure 7(a), (b) and (c) indicate the number of cycle slips per 1000 observation for ISK1, ISK2 and ISK3 respectively.

248 249 250 251 252 253 254 255 256 257 2580.01

0.011

0.012

0.013

0.014

0.015

Day of Year

Cycle Slips per 1000 observation of ISK1 Station

(a)

248 249 250 251 252 253 254 255 256 257 2580

0.02

0.04

0.06

0.08

0.1

Cycle Slips per 1000 observation of ISK2 Station

Day of Year (b)

248 249 250 251 252 253 254 255 256 257 2580.012

0.013

0.014

0.015

Day of Year

Cycle Slips per 1000 observation of ISK3 Station

(c)

Figure 7: Cycle Slips per 1000 Observation of Reference Stations

Results of cycle slips per 1000 observation of ISK1 retain 0.013 from Day of Year 249 to 257. The ISK3 also has same number of cycle slips per 1000 observation except on Day of Year 257, which is about 0.015. However, in case of ISK2, the number of cycle slips per 1000 observation varies from 0.012 to 0.107. This scenario is happen most probably due to relation of high multipath effect at ISK2 station rather than ISK1 and ISK3 stations. Generally, cycle slips refer to sudden phase jumps due to the satellite’s loss lock in phase

data. Loss lock may take place under circumstances such as the blocking of satellite signals by surrounding buildings, the influence of ionospheric and tropospheric events and some defect of the receiver itself (Leick, 2004). From site inspection of the reference stations, ISK2 has a nearby object located at ISK2’s antenna. 5.0 TESTS ON COMMUNICATION LINK AND NETWORK CORRECTION GENERATION OF ISKANDARnet Generally, there are two components of the data communication system: (a) between the control centre and the various reference stations, and (b) communication between the control centre and users (Rizos et al., 2004). For ISKANDARnet, the GPS data streaming from each reference station has been streamed to a control center via internet connection. The NTRIP software as illustrated in section 3.3 has been applied. Figure 8 shows that the NtripServer and the NtripClient applications being operated in ISK1, ISK2 and ISK3 for retrieving data.

 (a)  

                                                 (b)

Figure 8: Data stream via (a) NtripServer and (b) NtripClient. The stability of the data acquisition then has been tested for 5 days which on 26th – 30th August 2009. During the data streaming, there were internet disconnecting occurred. For instance in ISK2 station, it was happen randomly as can be seen in Table 2. The duration of lost connection is only in short period which range from 11 up to 37 second. However, there is a “reconnection setting” in NtripServer to reconnect back to NtripCaster. Test has also been conducted in ‘blackout’ scenario. It has been found that ISK2 source station attempted to reconnect to the NtripCaster and after awhile, the connection link of NtripServer at ISK2 was successfully backed to normal.

Table 2: Summary of discontinuity internet connection of ISKANDARnet2 station

Date Start of lost connection (hh:mm:ss)

Reconnected (hh:mm:ss)

Duration (second)

26/Aug/2009 16:16:59 16:17:36 37” 27/Aug/2009 02:32:45 02:32:59 14” 27/Aug/2009 14:33:16 14:33:27 11” 27/Aug/2009 15:13:49 15:14:00 11” 27/Aug/2009 16:54:16 16:54:28 12” 28/Aug/2009 22:58:50 22:59:14 24” 29/Aug/2009 22:59:10 22:59:23 13” 30/Aug/2009 10:22:10 10:22:23 13” 30/Aug/2009 17:00:07 17:00:18 11”

The stability of ISK2 has been monitored simultaneously with ISK1. However, there was lost connection occurred on 30 August 2009. It was probably because lost internet connection between ISK2 and control center in UTM (ISK1). Further investigation and solution need to be done soon to recover this problem. In the case of network corrections generation, all data streaming that retrieve from NtripCaster are used as input for data processing. In this test, the Multiple Reference Station (MRS) in the N-RTK software has been used and the ISK1 was selected as the master station.

 Figure 9: Network Corrections of ISKANDARnet

Figure 9 shows the network corrections have been successfully generated on a satellite-by-satellite basis in the MRS window. In this case, PRN 29 is automatically set as the reference satellite as it is the highest elevation satellite. Number of network corrections then was monitored. Figure 10 shows the number of network correction that generated during 5 hours on 2nd October 2009.

Figure 10: Number of Network Correction

Based on Figure 10, the numbers of network correction that generated from MRS are range from 3 to 9. The most number frequently occurs is 3. This circumstance happened probably due to the difficulty of network ambiguity resolution process. There are several important aspects for ambiguity resolution such as considering short baselines, good satellite geometry, and less multipath effects. Further step to examine efficiency of the network corrections need to be conducted. 6.0 CONCLUDING REMARKS & FUTURE WORKS The general idea of configuration an N-RTK system known as ISKANDARnet has been described. For instance, the infrastructure of the control centre and reference stations as well as communication links for data streaming have been configured. Data quality at every reference station has been checked by computing the value of RMS multipath effects on L1 and L2. Furthermore, verification on cycle slips has been conducted as part of data quality judgment. It was found that the multipath effect and number of cycle slips at ISK2 is higher than at ISK1 and ISK3. Essentially, the multipath effects of those stations are within acceptable limit. However multipath effect seems affect the number of cycle slips and network ambiguity resolution. The communication link between reference stations and control center also play crucial role in order to stream continuously GPS data and thus generate sufficient network corrections. Further tests are needed to carry out to deliver network corrections to users as well as to evaluate user’s positioning accuracy. More research activities by utilising ISKANDARnet system has expected gain knowledge and expose opportunity for various studies. This research facility is also important as operational platform for high precision applications within the metro-area of ISKANDAR Malaysia.

ACKNOWLEDGEMENTS The authors would like to express their gratitude to Ministry of Science, Technology and Innovation (MOSTI) Malaysia for their financial support throughout the project. REFERENCES Brown, N., Geisler, I. and Troyer, L. 2006. RTK Rover Performance using the Master-Auxiliary Concept. Journal of Global Positioning Systems. 5(1-2), 135-144. Bruyninx, C., Carpentier, G. and Roosbeek, F. 2003. Today’s EPN and its network coordination. EUREF Symposium, 4-6 June, Toledo, Spain. EUREF Publication, 13 (33), 38-49. Landau, H., Vollath, U., and Chen, X. Virtual Reference Station Systems. Journal of Global Positioning Systems. 2002.Vol. 1, No. 2: 137-143. Leick, A. 2004. GPS Satellite Survey 3rd edition. New York, Wiley. Lim, S. and Rizos, C. 2008. System Architecture for Server-Based Network-RTK using Multiple GNSS. Integrating Generations FIG Working Week, 14-19 June, Stockholm, Sweden. Musa, T.A. 2007. Analysis of residual atmospheric delay in the low latitude regions using network-based GPS positioning. Doctor of Philosophy thesis, School of Surveying & Spatial Information Systems, University of New South Wales, Sydney, Australia. Rizos, C. and Han, S. 2003. Reference station network based RTK systems-concepts and progress. Wuhan University Journal of Natural Sciences, 8 (2), p.p. 566-574. Rizos, C., Kinlyside, D.A., Yan, T.S., Omar, S. and Musa, T.A., 2003. Implementing network RTK: The SydNET CORS infrastructure. 6th Int. Symp. on Satellite Navigation Technology Including Mobile Positioning & Location Services, 22-25 July, Melbourne, Australia. Rizos, C., Yan, T.S. and Kinlyside, D.A. 2004. Development of SydNET permanent real-time GPS network. Journal of GPS, 3(1-2), p.p 296-301. Willgalis, S., Seeber, G., Krueger, C.P. and Romao, V. 2002. A real time GPS reference network for Recife, Brazil, enabling precise and reliable cadastral survey. FIG XXII International Congress, Technical Session 5.8. 19-26 April, Washington DC, USA. Wubbena, G., Bagge, A., and Schmitz, M. RTK Networks based on Geo++® GNSMART −Concepts, Implementation, Results. Presented at the International Technical Meeting, ION GPS−01, September 11.−14., 2001, Salt Lake City, Utah.

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