- Email: [email protected]
COMPASS data quality and its effect on single point positioning accuracy under different observing conditions
Available online at www.sciencedirect.com
Advances in Space Research xxx (2013) xxx–xxx www.elsevier.com/locate/asr
An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions Changsheng Cai a, Yang Gao b,c,⇑, Lin Pan a, Wujiao Dai a a
Department of Surveying and Geo-informatics, Central South University, Changsha 410083, China b School of Geomatics, Liaoning Technical University, Fuxin 123000, China c Department of Geomatics Engineering, University of Calgary, Calgary, Alberta, Canada T2N 1N4
Abstract With the rapid development of the COMPASS system, it is currently capable of providing regional navigation services. In order to test its data quality and performance for single point positioning (SPP), experiments have been conducted under different observing conditions including open sky, under trees, nearby a glass wall, nearby a large area of water, under high-voltage lines and under a signal transmitting tower. To assess the COMPASS data quality, the code multipath, cycle slip occurrence rate and data availability were analyzed and compared to GPS data. The datasets obtained from the experiments have also been utilized to perform combined GPS/COMPASS SPP on an epoch-by-epoch basis using unsmoothed single-frequency code observations. The investigation on the regional navigation performance aims at low-accuracy applications and all tests are made in Changsha, China, using the “SOUTH S82-C” GPS/COMPASS receivers. The results show that adding COMPASS observations can significantly improve the positioning accuracy of single-frequency GPS-only SPP in environments with limited satellite visibility. Since the COMPASS system is still in an initial operational stage, all results are obtained based on a fairly limited amount of data. Ó 2013 COSPAR. Published by Elsevier Ltd. All rights reserved. Keywords: GPS; COMPASS; Data quality; Single point positioning; Regional navigation service
1. Introduction COMPASS (BeiDou-2) is an independent global navigation satellite system (GNSS) that is being developed rapidly by China. The COMPASS system implementation has been made in three steps in terms of its deployment timeline (CSNO, 2011): BeiDou-1 navigation demonstration system by 2000, regional BeiDou-2 navigation satellite system by 2012 and global BeiDou-2 navigation satellite system by 2020. So far, the first step has been realized. For the second ⇑ Corresponding author at: Department of Geomatics Engineering, University of Calgary, Calgary, Alberta, Canada T2N 1N4. Tel.: +1 4032206174; fax: +1 4032841980. E-mail addresses: [email protected] (C. Cai), [email protected] (Y. Gao), [email protected] (L. Pan), [email protected] (W. Dai).
step, the constellation that comprises 5 Geostationary Orbit (GEO) satellites, 5 Inclined Geosynchronous Orbit (IGSO) satellites and 4 Medium Earth Orbit (MEO) is almost completed except for one MEO satellite (http:// www.beidou.gov.cn/). The COMPASS was declared on Dec.27, 2011 to provide regional navigation services in a commissioning phase. The constellation in the third step will consist of 5 GEO, 3 IGSO and 27 MEO satellites. Similar to GPS, the COMPASS MEO satellites have an inclination of 56.3° and a semi-major of 27,910 km. Currently, the COMPASS satellites are broadcasting signals on three frequencies, namely B1 centered at 1561.098 MHz, B2 at 1207.140 MHz and B3 at 1268.520 MHz (Shi et al., 2012; Gao et al., 2009). An additional frequency at 1589.74 MHz has not been employed yet. The chipping rate of the COMPASS B1 ranging code
0273-1177/$36.00 Ó 2013 COSPAR. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.asr.2013.02.019
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
2
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
is 2046 Kbps, which is twice as high as the chipping rate of GPS C/A code. The transmitted signal is modulated by Quadrature Phase Shift Keying (QPSK). The minimum received signal power level for the B1 ranging code is specified to be 163 dBW, which is 4.5 dBW lower than GPS C/A code (CSNO, 2012). Before the live COMPASS data are widely available for position determination, simulated COMPASS measurements are usually used to investigate the positioning performance using COMPASS (e.g., Grelier et al., 2007; Cao et al., 2008; Guo et al., 2011; Zhang et al., 2010). With live COMPASS data available, several researchers have recently investigated the COMPASS signal characteristics and the performance of precise point positioning (PPP) (Hauschild et al., 2012; Montenbruck et al., 2012; Li et al., 2012). As the content of the COMPASS navigation message is only available for limited investigators, little work about its navigation performance has been publicly reported. Shi et al. (2012) obtained COMPASS-alone navigation solutions with a three-dimensional position accuracy of approximate 20 m using data collected in June, 2011. However, as the results were obtained 6 months earlier than the time of declaring the regional navigation service capability, such an accuracy level may not represent the regional navigation accuracy with sufficient number of satellites. Since the COMPASS regional navigation performance is of interest to the GNSS user community, particularly for the integration of COMPASS and GPS, the combined GPS/COMPASS positioning performance in a single point positioning (SPP) mode is investigated here using data collected under different observing conditions in Changsha, China. An analysis of the COMPASS data quality is also made including the evaluation of the code multipath effect, cycle slip occurrence rate and data availability. 2. Data collection In order to assess the effects of satellite visibility, multipath and radio interference on the COMPASS data quality, Observation datasets were collected in six different observing conditions, i.e., open sky, under trees, nearby a glass wall, nearby a large area of water, under high-voltage lines and under a signal transmitting tower, as displayed in Fig. 1. The Fig. 1(a) is located on the roof of a tall building at the railway campus of the Central South University (CSU), China. There is no signal blockage around the receiver. Shown in Fig. 1(b) is an area of trees located before the Mining Building of the CSU. Some satellite signals will pass through the foliage before they can reach the receiver. Fig. 1(c) illustrates a glass building located before the Foreign Language Building at the new campus of the CSU. Some satellite signals will be reflected by the smooth glass wall and thus will cause multipath effects. Since the multipath effect can also be easily caused by calm water surfaces, shown in Fig. 1(d) is an artificial lake at the new campus of
the CSU. The receiver stations under the high-voltage lines and a signal transmitting tower are displayed in Fig. 1(e) and (f), respectively. The high-voltage lines have a voltage of approximate 10 kv with a height of about 6 m, located outside the north gate of the new campus at the CSU. The signal transmitting tower is about 400 m far away to the north gate in the west with a height of about 15 m. The horizontal distance between the station and the tower is about 10 m. The tower transmits signals on a 900 MHz frequency for cell phone users. The receivers used are two “SOUTH S82-C” receivers, manufactured by South Surveying and Mapping Instrument Inc., China. It adopts highly reliable carrier tracking technology and provides high-accuracy raw observations for users. It has 220 signal channels and supports COMPASS B1/B2 and GPS L1/L2 signal reception. Some channels are reserved for tracking GLONASS and GALILEO signals. The receivers can output observation data at 1 Hz. Its antenna is integrated with the receiver so no antenna cable is needed. The integrated receiver and antenna is shown in Fig. 2. The noise level of each receiver was assessed prior to the data acquisition and was found to be at the same level. Datasets were collected from the GPS Time 2:30–7:20 (Local time 8 h) on four different days. Specifically, the experiments in Fig. 1 (a) and (f) were made on July 23 and 24, 2012, respectively. The experiments in Fig. 1(c) and (e) were conducted on July 26, 2012. For Fig. 1(b) and (d), they were made on July 29, 2012. All observations were obtained at a sampling interval of 20 s. The elevation mask angle is set to 10°. During the test periods, six or seven COMPASS satellites were visible at these stations. Our investigations are based on raw observations that are downloaded from the receivers and no form of pseudorange code smoothing was applied. The tracked GPS pseudorange measurements refer to C/A and P2 on L1 and L2 frequencies, respectively. The GPS P2 code observations are obtained using semi-codeless tracking technology.
3. Quality analysis of GPS/COMPASS measurements The quality of the acquired data is analyzed in three aspects, namely the multipath effect, the cycle-slip occurrence rate and the data availability. For GPS, the multipath combinations of observations on the Li (i = 1, 2) frequencies have been widely utilized to evaluate the combined effect of the pseudorange multipath and the noise of a receiver. They may be expressed as (Estey and Meertens, 1999): MP 1 ¼ P 1 1 þ
2 2 U2 U1 þ a1 a1 2 2 m2 þ eP 1 ¼ M 1 þ C1 1 þ m1 þ a1 a1
ð1Þ
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
(a) Under open sky
(d) Nearby a large area of water
(b) Under trees
(e) Under high-voltage lines
3
(c) Nearby a glass wall
(f) Under a signal transmitting tower
Fig. 1. GPS/COMPASS data collection under different observing conditions.
Fig. 2. “SOUTH S82-C” receiver used for GPS/COMPASS data collection.
2a 2a U1 þ 1 U2 MP 2 ¼ P 2 a1 a1 2a 2a m1 þ 1 m2 þ eP 2 ¼ M 2 þ C2 a1 a1
ð2Þ
where a ¼ f12 =f22 ; MP1 and MP2 are the multipath combinations on L1 and L2 frequencies in meters, respectively; M is the multipath effect in the measured pseudorange in meters; m is the multipath effect in the measured carrier phase in meters; P is the measured pseudorange in meters; U is
the measured carrier phase in meters; f is the carrier-phase frequency in hertz; eP is the noise of the combined observations in meters; C is a sum of the combined ambiguity item and hardware delay biases, which will remain a constant as long as the phase observations are free of cycle slips and there is no loss of lock. In (1) and (2), the multipath combination is both ionosphere-free and geometry-free since the first-order ionosphere effect and geometry range between the satellite and the receiver are removed. The multipath combination is dominated by the code multipath and code noise as the carrier phase multipath and carrier phase noise is much smaller in magnitude. In this study, the multipath combination is used to assess the code multipath and noise level after eliminating its mean value. The mean value is computed every 15 epochs (5 min). When cycle slips occur, the computation is restarted from the cycle slip occurrence epoch. As the computation is dependent on the epoch that cycle slips occur, the cycle slips must be first detected. We have used the TurboEdit (Blewitt, 1990) algorithm to detect cycle slips. TurboEdit is an algorithm for cycle slip identification and repair as well as outlier removal using undifferenced, dual-frequency GPS data. The detection of cycle slips is based on the Melbourne–Wu¨bbena (M–W) combination (Melbourne, 1985; Wu¨bbena, 1985) and the geometry-free combinations with use of a recursive averaging filter. For simplicity, we do not
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
4
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
distinguish the specific frequency on which the cycle slip occurs. As long as a cycle slip is identified on either frequency, it is counted as one occurrence of a cycle slip at that epoch. In addition to code multipath and cycle slip occurrence rate, the data availability is also calculated to assess the data quality. When the pseudorange and carrier phase observations on both L1 and L2 frequencies are obtained at a certain epoch, it is considered that the observations are available at that epoch. For COMPASS, the code multipath, cycle slip occurrence rate and data availability are computed in a similar way. 3.1. Quality analysis of data collected under different visibility conditions Fig. 3 shows the multipath combinations on B1/L1 frequencies for all visible COMPASS and GPS satellites at the station in the open sky condition. Different colors represent different satellites. The station is located on the top of a high building so it is less affected by multipath effects. Therefore, the magnitude of the multipath combinations mainly reflects the code noise level. The STD (Standard Deviation) of the multipath combinations indicates that the GPS code observations have a noise level of 0.252 and 0.280 m on L1 and L2 frequencies, respectively. The COMPASS code observations have a comparable noise level of 0.246 and 0.317 m on B1 and B2 frequencies, respectively. These statistical values have been listed in Table 1. It is worthwhile to note that the statistical values are computed using all epoch data regardless of the difference in satellite elevation angles. General speaking, the noise level of the observations will increase as the satellite elevation angles decrease. In order to reflect the relation between the noise level and the elevation angles, the STD of multipath combinations is calculated with respect to the elevation angle change using an increment of 5° and the results are shown in Fig. 4. The STD at the 12.5° is a statistical value of the multipath combinations using all observations with elevation angles from 10° to 15°. The figure shows that the
COMPASS code noise on the B1 frequency is slightly larger than the GPS code noise on the L1 frequency whereas the COMPASS code observations on the B2 frequency have a significantly larger noise level than the GPS code observations on the L2 frequency. For both COMPASS and GPS, the noise level on the B1/L1 frequencies is smaller than that on the B2/L2 frequencies. It is noted that the STD value at the elevation angle of 32.5° is not available as there are no COMPASS observations at the elevation angles from 30° to 35°, as seen in Fig. 5. Fig. 5 illustrates the elevation angles of all visible COMPASS and GPS satellites at the station under open sky. During the entire test, the elevation angles of the GPS satellites vary from 10° to 90° whereas the COMPASS elevation angles change in a range of 20°–85°. Thus, the STD values of the multipath combinations with elevation angles below 20° and over 85° are unavailable for COMPASS in Fig. 4. Fig. 6 illustrates the STD of the multipath combinations for each COMPASS and GPS satellites. The noise level of the code observations on the B1/L1 frequencies is slightly smaller than that on the B2/L2 frequencies for all visible COMPASS and GPS satellites except the GPS satellites PRN 30 and PRN 11. The COMPASS satellite PRN 05 has a largest code noise level due to its low elevation angles. Shi et al. (2012) demonstrates that the GPS STDs vary in a range of 0.20–0.50 m while the COMPASS STDs are about 0.21–0.55 m using GPS/COMPASS receivers “UB240-CORS”. In terms of the variation ranges, the statistical values in Fig. 6 can match with their results well. But since observations were made at different locations with different receivers, the STD values for the same satellite are slightly different. The carrier-to-noise density ratio (C/N0) is defined as the ratio of the received carrier signal power to the received noise power, which indicates the quality of the received signal. The left plot of Fig. 7 depicts the mean values of C/N0 with respect to elevation angles with an increment of 5° for both GPS and COMPASS on two frequencies at the station under open sky. The C/N0 value is computed using the compressed signal strength value (i.e., 1–9) since the
Fig. 3. Multipath combinations on B1/L1 frequencies for all visible COMPASS and GPS satellites at the station under open sky.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
5
Table 1 STD of multipath combinations, cycle slip occurrence rate and data availability in six different observing conditions. MP1 (m) Open sky Trees Glass wall Water Signal tower High-voltage
MP2 (m)
Cycle-slips/observations (‰)
COM
GPS
COM
GPS
COM
GPS
COM
GPS
0.246 0.622 0.473 0.307 0.414 0.401
0.252 0.952 0.899 0.405 0.557 0.626
0.317 0.761 0.530 0.360 0.470 0.475
0.280 1.005 0.925 0.429 0.591 0.676
0.695 1.504 1.209 0.747 1.256 1.169
0.437 8.772 1.383 0.539 1.321 1.170
99 90 94 97 93 96
96 79 86 93 87 92
0.5
0.5
COM B2
0.4
GPS L1 GPS L2
0.3
Multipath (m)
COM B1
0.4
COMPASS
B1
B2
0.3 0.2 0.1 0 01
0.1
0 10
03
04
05
07
08
10
0.5
0.2 Multipath (m)
Multipath (m)
Data availability (%)
20
30
40 50 60 Elevation (degree)
70
80
90
0.4
GPS
L1
L2
0.3 0.2 0.1 0 01 03 06 07 08 11 13 14 16 19 20 23 30 31 32 Satellite PRN
Fig. 4. STD of multipath combinations over elevation angles for all visible COMPASS and GPS satellites on B1/L1 and B2/L2 frequencies at the station under open sky.
Fig. 6. STD of multipath combinations for each COMPASS and GPS satellites at the station under open sky.
original signal strength measurements are not available from the observation file. It can be seen that the C/N0 values on the COMPASS B1 frequency is slightly lower than that on the GPS L1 frequency whereas the C/N0 values on the COMPASS B2 frequency is significantly higher than that on the GPS L2 frequency at elevation angles of below 60°. To test the code multipath effect and the noise level in a poor satellite visibility condition, the multipath combination values are computed using the dataset collected under trees. Fig. 8 shows the multipath combinations for all
visible COMPASS and GPS satellites. In contrast to Fig. 3, the multipath combinations vary in a larger range for both COMPASS and GPS during the entire test. For COMPASS satellites, the STDs of the multipath combinations are 0.622 and 0.761 m on the B1 and B2 frequencies, respectively. Nevertheless, the STDs of the GPS multipath combinations are larger on both L1 and L2 frequencies. They are 0.952 and 1.005 m, respectively, as shown in Table 1. The COMPASS STD values are over two times larger than those obtained in the station under open sky while the GPS STD values are over three times larger. This
Fig. 5. Elevation angles for all visible COMPASS and GPS satellites at the station under open sky.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
6
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx Under trees
45
40
40
35
35
30 COM B1
25
COM B2
C/N0 (dB-Hz)
C/N0 (dB-Hz)
Under open sky
45
30 COM B1
25
COM B2
GPS L1
20 15 10
20
30
40 50 60 Elevation (degree)
70
80
GPS L1
20
GPS L2
90
15 10
GPS L2
20
30
40 50 60 Elevation (degree)
70
80
90
Fig. 7. Carrier-to-noise density ratios of the “SOUTH S82-C” receivers for GPS and COMPASS signals.
Fig. 8. Multipath combinations on B1/L1 frequencies for all visible COMPASS and GPS satellites at the station under trees.
suggests a significantly larger multipath effect and noise level caused by the diffraction and reflection of the satellite signals when they pass through the trees. The mean values of C/N0 at the station under trees are provided in the right plot of Fig. 7. Comparing with the left plot in Fig. 7, it is found that the C/N0 values for both GPS and COMPASS are slightly smaller than their corresponding
values in the open sky condition when the elevation angles are below 60°. Fig. 9 shows the cycle slip detection results for all observed GPS and COMPASS satellites at the station under trees. The identified cycle slip is marked with a small red circle. Different colors are adopted to distinguish signals at different satellite elevation angles. It is obvious that
Fig. 9. Cycle slip identification for all visible COMPASS and GPS satellites at the station under trees.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
the low elevation angle signals more easily suffer from cycle slips. Since most COMPASS satellites are observed in a relatively high elevation angles, its cycle slip occurrence rate is much lower than GPS in the limited satellite visibility condition. In addition to the larger multipath effect and noise level under the condition with limited satellite visibility, the cycle slip occurrence rates of 1.504‰ and 8.772‰ for COMPASS and GPS are much larger than those in the open sky condition which are 0.695‰ and 0.437‰, respectively, as provided in Table 1. Further, the data availability is also lower. Under the tree condition the data availability is 90% and 79% for COMPASS and GPS whereas they are 99% and 96% under the open sky condition, respectively. In terms of the cycle slip occurrence rate and the data availability, the COMPASS data outweigh GPS data because most COMPASS data are collected at relatively larger elevation angles.
3.2. Quality analysis of data collected under different multipath conditions In order to test the multipath effect, datasets were collected at the stations nearby a glass wall and a large area of water, respectively. Fig. 10 shows the multipath combinations on B1/L1 frequencies for all visible COMPASS and GPS satellites at the station nearby the glass wall. For COMPASS, the larger multipath combination values are mainly from satellite C07. Their maximum value exceeds 2 m during the GPS time of 5:30–7:20. The multipath combination values obtained from other COMPASS satellites mostly vary in a range of 1 m. By contrast, the GPS multipath combination values have a larger variation during the test period. Their maximum value even exceeds 4 m. The STD statistical values are 0.473 and 0.530 m for COMPASS and 0.899 and 0.925 m for GPS on two frequencies, respectively. It appears that more GPS observations undergo the multipath effect. This is because more GPS satellites are faced to the glass wall at low elevation angles
7
and thus their signals are partly reflected by the glass wall prior to reaching the receiver antenna. Another experiment was conducted nearby a calm lake, which easily reflects satellite signals and causes multipath effects. The multipath combinations on the B1/L1 frequencies for all visible COMPASS and GPS satellites are significantly smaller than those shown in Fig. 10. This is because that the modernized GNSS antenna is designed to mitigate the multipath effect by resisting the ground-reflected satellite signals. The STD statistical values are 0.307 and 0.360 m for COMPASS and 0.405 and 0.429 m for GPS on two frequencies, respectively. These values are slightly larger than those in the open sky condition, as seen in Table 1. 3.3. Quality analysis of data collected under different radio interference conditions In order to test the multipath effect in the radio interference conditions, experiments were carried out under a signal transmitting tower and high-voltage lines, respectively. Fig. 11 illustrates the multipath combinations on the B1/L1 frequencies for all visible COMPASS and GPS satellites at the station under a signal transmitting tower. In contrast to Fig. 3, it is clear that the radio interference indeed has an impact on the multipath combinations. The multipath combinations at the station under high-voltage lines are similar to those displayed in Fig. 11. Under the two radio interference conditions, the STD values of the multipath combinations are over 0.15 m larger for COMPASS and over 0.3 m larger for GPS on both frequencies than those under the open sky condition. The STD of multipath combinations, the cycle slip occurrence rate and the data availability in all six observing conditions have been provided in Table 1. It is noted that the “under trees” observing condition significantly increases the occurrence rate of cycle slips and decreases the data availability when compared with other observing conditions. In terms of multipath effect, cycle slips and data acquisition, the data quality in the station nearby a large
Fig. 10. Multipath combinations on B1/L1 frequencies for all visible COMPASS and GPS satellites at the station nearby a glass wall.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
8
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
Fig. 11. Multipath combinations on B1/L1 frequencies for all visible COMPASS and GPS satellites at the station under a signal transmitting tower.
area of water is the second best, following the data quality under the open sky condition. 4. Analysis on combined GPS/COMPASS single point positioning solutions As stated in the previous section, the pseudorange measurements are influenced by different magnitudes of multipath and noise under different observing conditions. In order to analyze their effects on SPP solutions, the same datasets collected in the six different observing conditions are used in post-mission to perform SPP in a combined GPS/COMPASS dual-system mode and a GPS-only single-system mode. The GPS PPP (Zumberge et al., 1997) solutions are used as coordinate references to assess the accuracy of the pseudorange-based SPP in the east, north and up directions. The P3 software package that is developed at the University of Calgary is used for the SPP and PPP processings. Since most SPP users are operating single-frequency receivers, only the pseudorange measurements on the B1/L1 frequencies are used. The ionospheric and tropospheric delay errors are corrected using the Klobuchar and Saastamoinen models, respectively. The satellite position and clock offset are computed using the broadcast ephemeris data. The COMPASS system adopts the Chinese Geodetic Coordinate System 2000 (CGCS2000) coordinate system, which is consistent with the International Terrestrial Reference Frame 1997 with a difference of about 3 cm (Shi et al., 2012). As a result, the difference between CGCS2000 and WGS-84 (GPS coordinate system) is only at a level of a few centimeters. Such a small difference in the coordinate references is negligible in our analysis of the pseudorange-based SPP performance. Thus, the coordinate transformation is not necessary in the combined GPS/ COMPASS SPP. In addition to the difference in the coordinate system, the COMPASS system has adopted an independent COMPASS Timing System (BDT), which differs from the UTC (Coordinated Universal Time) with a fractional second difference of smaller than 100 ns (CSNO, 2011). This accuracy is similar for the difference of GPS
Time and UTC (IS-GPS-200F, 2011). As a result, an additional unknown parameter is needed to estimate the system time difference between COMPASS and GPS along with the three coordinate components and one receiver clock offset in the combined GPS/COMPASS SPP. In order to analyze the positioning accuracy, the position coordinates at each epoch are independently estimated using the Least Squares method. In the combined GPS/COMPASS SPP, a crucial issue is how to set a proper weight between GPS and COMPASS pseudorange observations. For COMPASS, the residual satellite orbit and clock errors after using the broadcast ephemeris data are unclear so far. This will cause difficulty in assigning proper weights to GPS and COMPASS observations. In the implementation of the combined GPS/ COMPASS SPP, the initial variances of the GPS and COMPASS observations need to be provided to the Least Squares adjustment, which will be applied to determine the initial weight of the observations from two different GNSS systems. The actual variances will still take elevation angles into account and the weights assigned to observations are elevation dependent. Since there is no available reference regarding the setting of proper initial weights, we have used four different scenarios for initial weights, i.e., 1:1, 4:1, 9:1 and 16:1 (GPS versus COMPASS) in our performance analysis. The STDs of the GPS code observations are set to 0.3 m for all four scenarios while the STDs of the COMPASS code observations are set to 0.3, 0.6, 0.9 and 1.2 m, respectively. Table 2 lists the RMS (Root Mean Square) statistics of the positioning errors for the combined GPS/COMPASS Table 2 RMS statistics of positioning errors for combined GPS/COMPASS single point positioning using four different scenarios (m). Weights
East
North
Up
3-D
1:1 4:1 9:1 16:1
1.246 1.348 1.357 1.363
3.160 2.362 2.350 2.345
6.041 4.436 4.330 4.281
6.930 5.204 5.111 5.068
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
COM. Residual (m)
GPS Residual (m)
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx 6 3 0 -3 -6 6 3 0 -3 -6 3:30
4:30
5:30
6:30
GPS Time (HH:MM)
Fig. 12. GPS vs. COMPASS code observation residuals for the combined GPS/COMPASS SPP processing on B1/L1 frequencies.
Table 3 RMS statistics of GPS and COMPASS code residuals for combined GPS/ COMPASS single point positioning using four different scenarios (m). Weights
GPS residual
COMPASS residual
1:1 4:1 9:1 16:1
1.105 1.002 0.992 0.991
1.117 1.344 1.427 1.464
SPP processings based on the four different scenarios for initial weights using the dataset collected under the open sky condition. The RMS values suggest that an initial
9
weight of 1:1 between GPS and COMPASS is not proper since the three-dimensional positioning accuracy are significantly lower than the other three scenarios. When the initial weights of 4:1, 8:1 and 16:1 are used, there is no significant difference among the position solutions, which can also be seen from the RMS values. Since the improvement of the positioning accuracy is not significant when the initial weight is increased from 4:1 to 16:1, an initial weight of 4:1 between GPS and COMPASS is therefore adopted in the following data processing to avoid further decreasing the contribution of COMPASS observations to the positioning solution. Fig. 12 shows the GPS and COMPASS code observation residuals on the B1/L1 frequencies for the combined GPS/ COMPASS SPP processing in an initial weight setting of 4:1 using the dataset collected in the open sky condition. Different colors represent different satellites. It can be seen that most GPS residuals vary in a range of 2–2 m whereas most COMPASS residuals are in a wider range of 3–3 m. In contrast to GPS, the COMPASS residuals for each satellite remain fairly stable. This is because some tracked COMPASS satellites belong to GEO satellites whose elevation angles almost never change and the other COMPASS satellites are at relatively high elevation angles during the observation time, as seen in Fig. 5. The RMS statistical values of GPS and COMPASS residuals are listed in Table 3 with respect to the different initial weight settings. It can be seen that residual errors are increased in the COMPASS code observations and the residual errors in the GPS code observations are reduced when the initial weight changes from 1:1 to 4:1. As a result, the positioning accuracy is increased,
Under open sky
Under trees
East (m)
7 0
Up (m)
North (m)
-7 7
GP S GP S/COM
0 -7 20 0
Num. of sats.
PDOP
-20 4 2
15 5 3:30
4:30
5:30
6:30 3:30
4:30
5:30
6:30
GPS Time (HH:MM)
Fig. 13. GPS/COMPASS vs. GPS-only positioning errors of single point positioning in different satellite visibility conditions.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
10
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
Table 4 RMS statistical results of position errors in different observing conditions (m).
GPS-only
GPS/COM
East North Up 3-D East North Up 3-D
Open sky
Trees
Glass wall
Water
High-voltage
Signal tower
1.375 2.336 4.252 5.043 1.348 2.362 4.436 5.204
2.900 3.157 7.979 9.058 1.499 2.809 5.719 6.535
1.893 2.782 6.660 7.461 1.488 2.665 5.120 5.960
1.404 2.415 4.423 5.232 1.327 2.471 4.487 5.291
1.548 2.522 4.757 5.602 1.331 2.510 4.694 5.481
1.653 2.601 5.560 6.357 1.418 2.560 4.983 5.778
Under trees East (m)
7 0
Up (m)
North (m)
-7 7 0 -7 20
GPS GPS/COM
0
Num. of sats.
PDOP
-20 4 2
15 5 1:30
2:30
3:30
4:30 6:30
7:30
8:30
9:30
GPS Time (HH:MM)
Fig. 14. GPS/COMPASS vs. GPS-only positioning errors of single point positioning in the limited satellite visibility condition on October 23, 2012.
as shown in Table 2. When the initial weight is further increased, the variation in the GPS and COMPASS code residuals becomes very small. This indicates that the positioning accuracy cannot be further improved significantly. This explains again why an initial weight of 4:1 was adopted for the combined GPS/COMPASS SPP processings. Fig. 13 shows a comparison between the GPS/COMPASS and GPS-only position errors for SPP under different satellite visibility conditions. In the open sky condition, the average number of GPS satellites is 8.9. After adding 7 COMPASS satellites, the improvement on the satellite geometry is not significant. As a result, the combined GPS/COMPASS SPP does not improve the positioning accuracy over the GPS-only SPP. But for the station under trees, the positioning accuracy has been significantly improved by adding COMPASS data due to the improvement of the satellite geometry, especially over the period of 4:25–4:55. During this period, the maximum PDOP (Position Dilution of Precision) value reaches 6.1
due to a minimum of 5 satellites for GPS-only case but the maximum PDOP value is reduced to 3.0 after adding 6 COMPASS satellites. As a result, the largest positioning errors of 27.838, 13.659 and 52.326 m in the east, north and up directions are reduced to 5.884, 4.631 and 12.058 m after adding the COMPASS data. As most COMPASS satellites are tracked at high elevation angles, their signals are less blocked by the nearby trees. Table 4 lists the RMS statistical results of position errors at the stations under open sky and trees. In terms of three-dimensional position accuracy, the improvement is 28% at the station under trees. The COMPASS-only observations are used for SPP processing and RMS statistical results of positioning errors indicate an accuracy of 1.121, 3.928, and 8.011 m in the east, north, and up directions in the open sky condition, respectively. Comparing to GPS-only and GPS/COMPASS solutions, the COMPASS-only positioning accuracy is significantly lower, especially in the vertical component.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
The datasets collected in the multipath and radio interference conditions are also used for combined GPS/COMPASS and GPS-only SPP processings. Their RMS statistical results of position errors are also listed in Table 4. Table 4 indicates that the SPP positioning accuracy receives the biggest improvement from combining GPS and COMPASS for the station under trees where GPS satellite signals were partly blocked. The combined use of GPS and COMPASS increases the number of satellites and improves the satellite geometry. As a result, the positioning accuracy is improved. Comparing other RMS values with those in the open sky condition, it is found that the relatively poorer data quality in the multipath and radio interference conditions indeed has an impact on the positioning accuracy. To further validate the improvement that can bring by COMPASS data for positioning in the limited satellite visibility condition, an additional experiment was carried out in two sessions on October 23, 2012. The station is still located in an area of trees where the satellite signals are easily blocked by trees. Fig. 14 displays a comparison between the GPS/COMPASS and GPS-only position errors for SPP processing. Similar to the right plot of Fig. 13, the improvement on all three components are significant, especially for those epochs with large GPS-only positioning errors. The number of satellites and PDOP clearly demonstrate that the positioning accuracy improvement attributes to more visible satellites and improved satellite geometry. The RMS of GPS-only position errors indicates an accuracy of 2.723, 3.293 and 7.779 m in the east, north and up components while the corresponding RMS of GPS/COMPASS position errors are 1.683, 2.753 and 5.743 m, respectively. The improvement of the three-dimensional position accuracy reaches 26%, which is slightly lower than 28% as indicated in the right plot of Fig. 13. 5. Conclusions The COMPASS system presently consists of 13 operational satellites and has started to provide regional navigation services since December, 2011. We have tested its data quality and its positioning performance using two dualfrequency “SOUTH S82-C” GPS/COMPASS receivers to collect data under different observing conditions, namely, under open sky, under trees, nearby a glass wall, nearby a large area of water, under high-voltage lines and under a signal transmitting tower, respectively. All experiments are conducted in Changsha, China. In terms of the code multipath, cycle slip occurrence rate and data availability, the results with the test data have indicated better data quality for COMPASS in almost all observing conditions in comparison to GPS. This is primarily due to the fact that most COMPASS satellites are at relatively higher elevation angles. Further analysis over different elevation angles indicates that the COMPASS code noise on the B1 frequency has a comparable noise level to the GPS code observations on the L1 frequency whereas the B2 code observations have
11
a significantly larger noise level than the GPS L2 code observations. The same datasets under all six different observing conditions have been used to conduct combined GPS/COMPASS single point positioning (SPP). The result illustrates that the combined GPS/COMPASS SPP can significantly improve the positioning accuracy over the GPS-only SPP solutions under observing environments with signal attenuation. The results also nicely illustrate the impact of the multipath and radio interference on the accuracy of SPP solutions. Since the COMPASS system is still in an initial operational stage, all results are obtained based on a fairly limited amount of data. Acknowledgements The financial supports from NSFC (National Natural Science Foundation of China, No: 41004011) and Advanced Research Plan of Central South University (No: 2009QZZD002) are greatly appreciated. References Blewitt, G. An automatic editing algorithm for GPS data. Geophys. Res. Lett. 17 (3), 199–202, 1990. Cao, W., O’Keefe, K., Cannon, M.E. Evaluation of COMPASS ambiguity resolution performance using geometric-based techniques with comparison to GPS and Galileo, in: Proceedings of ION GNSS 2008, September 16–19, Savannah, Georgia, pp. 1688–1697, 2008. CSNO (China Satellite Navigation Office). BeiDou navigation satellite system signal in space interface control document (Test version), December 2011. CSNO (China Satellite Navigation Office). BeiDou navigation satellite system signal in space interface control document (open service signal B1I), Version 1.0, December 2012. Estey, L.H., Meertens, C.M. TEQC: the multi-purpose toolkit for GPS/ GLONASS data. GPS Solution 3 (1), 42–49, http://dx.doi.org/ 10.1007/PL00012778, 1999. Gao, G.X., Chen, A., Lo, S., De Lorenzo, D., Walter, T., Enge, P. Compass-M1 broadcast codes in E2, E5b, and E6 frequency bands. IEEE J. Sel. Top. Signal Process 3 (4), 599–612, http://dx.doi.org/ 10.1109/JSTSP.2009.2025635, 2009. Grelier, T., Ghion, A., Dantepal, J., Ries, L., Delatour, A., AvilaRodriguez, J.A., Wallner, S., Hein, G.W. COMPASS signal structure and first measurements, in: Proceedings of ION GNSS 2007, September 25–28, Fort Worth, Texas, pp. 3015–3024, 2007. Guo, H., He, H., Li, J., Wang, A. Estimation and mitigation of the main errors for centimetre-level Compass RTK solutions over medium-long baselines. J. Navig. 64, S113–S126, http://dx.doi.org/10.1017/ S0373463311000324, 2011. Hauschild, A., Montenbruck, O., Sleewaegen, J.M., Huisman, L., Teunissen, P.J.G. Characterization of COMPASS M-1 signals. GPS Solution 16 (1), 117–126, http://dx.doi.org/10.1007/s10291-011-02103, 2012. IS-GPS-200F. Global positioning system directorate systems engineering and integration interface specification, September 21, 2011. Li, X., Ge, M., Zhang, H., Nischan, T., Wickert, J. The GFZ real-time GNSS precise positioning service system and its adaption for COMPASS. Adv. Space Res. http://dx.doi.org/10.1016/j.asr.2012.06.025, 2012. Melbourne, W.G. The case for ranging in GPS based geodetic systems, in: Proceedings of the 1st international symposium on precise positioning with the global positioning system, Rockville, Maryland, pp. 373–386, 1985.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
12
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
Montenbruck, O., Hauschild, A., Steigenberger, P., Hugentobler, U., Teunissen, P., Nakamura, S. Initial assessment of the COMPASS/ BeiDou-2 regional navigation satellite system. GPS Solution, http:// dx.doi.org/10.1007/s10291-012-0272-x, 2012. Shi, C., Zhao, Q., Hu, Z., Liu, J. Precise relative positioning using real tracking data from COMPASS GEO and IGSO satellites. GPS Solution, http://dx.doi.org/10.1007/s10291-012-0264-x, 2012. Wu¨bbena, G. Software developments for geodetic positioning with GPS using TI 4100 code and carrier measurements, in: Proceedings of the 1st international symposium on precise positioning with
the global positioning system, Rockville, Maryland, pp. 403–412, 1985. Zhang, S., Guo, J., Li, B., Rizos, C. An analysis of satellite visibility and relative positioning precision of COMPASS, in: Symposium for Chinese Professionals in GPS, Shanghai, China, August 18–20, pp. 41–46, 2010. Zumberge, J.F., Heflin, M.B., Jefferson, D.C., Watkins, M.M., Webb, F.H. Precise point positioning for the efficient and robust analysis of GPS data from large networks. J. Geophys. Res. 102 (B3), 5005–5017, http://dx.doi.org/10.1029/96JB03860, 1997.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
Advances in Space Research xxx (2013) xxx–xxx www.elsevier.com/locate/asr
An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions Changsheng Cai a, Yang Gao b,c,⇑, Lin Pan a, Wujiao Dai a a
Department of Surveying and Geo-informatics, Central South University, Changsha 410083, China b School of Geomatics, Liaoning Technical University, Fuxin 123000, China c Department of Geomatics Engineering, University of Calgary, Calgary, Alberta, Canada T2N 1N4
Abstract With the rapid development of the COMPASS system, it is currently capable of providing regional navigation services. In order to test its data quality and performance for single point positioning (SPP), experiments have been conducted under different observing conditions including open sky, under trees, nearby a glass wall, nearby a large area of water, under high-voltage lines and under a signal transmitting tower. To assess the COMPASS data quality, the code multipath, cycle slip occurrence rate and data availability were analyzed and compared to GPS data. The datasets obtained from the experiments have also been utilized to perform combined GPS/COMPASS SPP on an epoch-by-epoch basis using unsmoothed single-frequency code observations. The investigation on the regional navigation performance aims at low-accuracy applications and all tests are made in Changsha, China, using the “SOUTH S82-C” GPS/COMPASS receivers. The results show that adding COMPASS observations can significantly improve the positioning accuracy of single-frequency GPS-only SPP in environments with limited satellite visibility. Since the COMPASS system is still in an initial operational stage, all results are obtained based on a fairly limited amount of data. Ó 2013 COSPAR. Published by Elsevier Ltd. All rights reserved. Keywords: GPS; COMPASS; Data quality; Single point positioning; Regional navigation service
1. Introduction COMPASS (BeiDou-2) is an independent global navigation satellite system (GNSS) that is being developed rapidly by China. The COMPASS system implementation has been made in three steps in terms of its deployment timeline (CSNO, 2011): BeiDou-1 navigation demonstration system by 2000, regional BeiDou-2 navigation satellite system by 2012 and global BeiDou-2 navigation satellite system by 2020. So far, the first step has been realized. For the second ⇑ Corresponding author at: Department of Geomatics Engineering, University of Calgary, Calgary, Alberta, Canada T2N 1N4. Tel.: +1 4032206174; fax: +1 4032841980. E-mail addresses: [email protected] (C. Cai), [email protected] (Y. Gao), [email protected] (L. Pan), [email protected] (W. Dai).
step, the constellation that comprises 5 Geostationary Orbit (GEO) satellites, 5 Inclined Geosynchronous Orbit (IGSO) satellites and 4 Medium Earth Orbit (MEO) is almost completed except for one MEO satellite (http:// www.beidou.gov.cn/). The COMPASS was declared on Dec.27, 2011 to provide regional navigation services in a commissioning phase. The constellation in the third step will consist of 5 GEO, 3 IGSO and 27 MEO satellites. Similar to GPS, the COMPASS MEO satellites have an inclination of 56.3° and a semi-major of 27,910 km. Currently, the COMPASS satellites are broadcasting signals on three frequencies, namely B1 centered at 1561.098 MHz, B2 at 1207.140 MHz and B3 at 1268.520 MHz (Shi et al., 2012; Gao et al., 2009). An additional frequency at 1589.74 MHz has not been employed yet. The chipping rate of the COMPASS B1 ranging code
0273-1177/$36.00 Ó 2013 COSPAR. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.asr.2013.02.019
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
2
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
is 2046 Kbps, which is twice as high as the chipping rate of GPS C/A code. The transmitted signal is modulated by Quadrature Phase Shift Keying (QPSK). The minimum received signal power level for the B1 ranging code is specified to be 163 dBW, which is 4.5 dBW lower than GPS C/A code (CSNO, 2012). Before the live COMPASS data are widely available for position determination, simulated COMPASS measurements are usually used to investigate the positioning performance using COMPASS (e.g., Grelier et al., 2007; Cao et al., 2008; Guo et al., 2011; Zhang et al., 2010). With live COMPASS data available, several researchers have recently investigated the COMPASS signal characteristics and the performance of precise point positioning (PPP) (Hauschild et al., 2012; Montenbruck et al., 2012; Li et al., 2012). As the content of the COMPASS navigation message is only available for limited investigators, little work about its navigation performance has been publicly reported. Shi et al. (2012) obtained COMPASS-alone navigation solutions with a three-dimensional position accuracy of approximate 20 m using data collected in June, 2011. However, as the results were obtained 6 months earlier than the time of declaring the regional navigation service capability, such an accuracy level may not represent the regional navigation accuracy with sufficient number of satellites. Since the COMPASS regional navigation performance is of interest to the GNSS user community, particularly for the integration of COMPASS and GPS, the combined GPS/COMPASS positioning performance in a single point positioning (SPP) mode is investigated here using data collected under different observing conditions in Changsha, China. An analysis of the COMPASS data quality is also made including the evaluation of the code multipath effect, cycle slip occurrence rate and data availability. 2. Data collection In order to assess the effects of satellite visibility, multipath and radio interference on the COMPASS data quality, Observation datasets were collected in six different observing conditions, i.e., open sky, under trees, nearby a glass wall, nearby a large area of water, under high-voltage lines and under a signal transmitting tower, as displayed in Fig. 1. The Fig. 1(a) is located on the roof of a tall building at the railway campus of the Central South University (CSU), China. There is no signal blockage around the receiver. Shown in Fig. 1(b) is an area of trees located before the Mining Building of the CSU. Some satellite signals will pass through the foliage before they can reach the receiver. Fig. 1(c) illustrates a glass building located before the Foreign Language Building at the new campus of the CSU. Some satellite signals will be reflected by the smooth glass wall and thus will cause multipath effects. Since the multipath effect can also be easily caused by calm water surfaces, shown in Fig. 1(d) is an artificial lake at the new campus of
the CSU. The receiver stations under the high-voltage lines and a signal transmitting tower are displayed in Fig. 1(e) and (f), respectively. The high-voltage lines have a voltage of approximate 10 kv with a height of about 6 m, located outside the north gate of the new campus at the CSU. The signal transmitting tower is about 400 m far away to the north gate in the west with a height of about 15 m. The horizontal distance between the station and the tower is about 10 m. The tower transmits signals on a 900 MHz frequency for cell phone users. The receivers used are two “SOUTH S82-C” receivers, manufactured by South Surveying and Mapping Instrument Inc., China. It adopts highly reliable carrier tracking technology and provides high-accuracy raw observations for users. It has 220 signal channels and supports COMPASS B1/B2 and GPS L1/L2 signal reception. Some channels are reserved for tracking GLONASS and GALILEO signals. The receivers can output observation data at 1 Hz. Its antenna is integrated with the receiver so no antenna cable is needed. The integrated receiver and antenna is shown in Fig. 2. The noise level of each receiver was assessed prior to the data acquisition and was found to be at the same level. Datasets were collected from the GPS Time 2:30–7:20 (Local time 8 h) on four different days. Specifically, the experiments in Fig. 1 (a) and (f) were made on July 23 and 24, 2012, respectively. The experiments in Fig. 1(c) and (e) were conducted on July 26, 2012. For Fig. 1(b) and (d), they were made on July 29, 2012. All observations were obtained at a sampling interval of 20 s. The elevation mask angle is set to 10°. During the test periods, six or seven COMPASS satellites were visible at these stations. Our investigations are based on raw observations that are downloaded from the receivers and no form of pseudorange code smoothing was applied. The tracked GPS pseudorange measurements refer to C/A and P2 on L1 and L2 frequencies, respectively. The GPS P2 code observations are obtained using semi-codeless tracking technology.
3. Quality analysis of GPS/COMPASS measurements The quality of the acquired data is analyzed in three aspects, namely the multipath effect, the cycle-slip occurrence rate and the data availability. For GPS, the multipath combinations of observations on the Li (i = 1, 2) frequencies have been widely utilized to evaluate the combined effect of the pseudorange multipath and the noise of a receiver. They may be expressed as (Estey and Meertens, 1999): MP 1 ¼ P 1 1 þ
2 2 U2 U1 þ a1 a1 2 2 m2 þ eP 1 ¼ M 1 þ C1 1 þ m1 þ a1 a1
ð1Þ
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
(a) Under open sky
(d) Nearby a large area of water
(b) Under trees
(e) Under high-voltage lines
3
(c) Nearby a glass wall
(f) Under a signal transmitting tower
Fig. 1. GPS/COMPASS data collection under different observing conditions.
Fig. 2. “SOUTH S82-C” receiver used for GPS/COMPASS data collection.
2a 2a U1 þ 1 U2 MP 2 ¼ P 2 a1 a1 2a 2a m1 þ 1 m2 þ eP 2 ¼ M 2 þ C2 a1 a1
ð2Þ
where a ¼ f12 =f22 ; MP1 and MP2 are the multipath combinations on L1 and L2 frequencies in meters, respectively; M is the multipath effect in the measured pseudorange in meters; m is the multipath effect in the measured carrier phase in meters; P is the measured pseudorange in meters; U is
the measured carrier phase in meters; f is the carrier-phase frequency in hertz; eP is the noise of the combined observations in meters; C is a sum of the combined ambiguity item and hardware delay biases, which will remain a constant as long as the phase observations are free of cycle slips and there is no loss of lock. In (1) and (2), the multipath combination is both ionosphere-free and geometry-free since the first-order ionosphere effect and geometry range between the satellite and the receiver are removed. The multipath combination is dominated by the code multipath and code noise as the carrier phase multipath and carrier phase noise is much smaller in magnitude. In this study, the multipath combination is used to assess the code multipath and noise level after eliminating its mean value. The mean value is computed every 15 epochs (5 min). When cycle slips occur, the computation is restarted from the cycle slip occurrence epoch. As the computation is dependent on the epoch that cycle slips occur, the cycle slips must be first detected. We have used the TurboEdit (Blewitt, 1990) algorithm to detect cycle slips. TurboEdit is an algorithm for cycle slip identification and repair as well as outlier removal using undifferenced, dual-frequency GPS data. The detection of cycle slips is based on the Melbourne–Wu¨bbena (M–W) combination (Melbourne, 1985; Wu¨bbena, 1985) and the geometry-free combinations with use of a recursive averaging filter. For simplicity, we do not
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
4
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
distinguish the specific frequency on which the cycle slip occurs. As long as a cycle slip is identified on either frequency, it is counted as one occurrence of a cycle slip at that epoch. In addition to code multipath and cycle slip occurrence rate, the data availability is also calculated to assess the data quality. When the pseudorange and carrier phase observations on both L1 and L2 frequencies are obtained at a certain epoch, it is considered that the observations are available at that epoch. For COMPASS, the code multipath, cycle slip occurrence rate and data availability are computed in a similar way. 3.1. Quality analysis of data collected under different visibility conditions Fig. 3 shows the multipath combinations on B1/L1 frequencies for all visible COMPASS and GPS satellites at the station in the open sky condition. Different colors represent different satellites. The station is located on the top of a high building so it is less affected by multipath effects. Therefore, the magnitude of the multipath combinations mainly reflects the code noise level. The STD (Standard Deviation) of the multipath combinations indicates that the GPS code observations have a noise level of 0.252 and 0.280 m on L1 and L2 frequencies, respectively. The COMPASS code observations have a comparable noise level of 0.246 and 0.317 m on B1 and B2 frequencies, respectively. These statistical values have been listed in Table 1. It is worthwhile to note that the statistical values are computed using all epoch data regardless of the difference in satellite elevation angles. General speaking, the noise level of the observations will increase as the satellite elevation angles decrease. In order to reflect the relation between the noise level and the elevation angles, the STD of multipath combinations is calculated with respect to the elevation angle change using an increment of 5° and the results are shown in Fig. 4. The STD at the 12.5° is a statistical value of the multipath combinations using all observations with elevation angles from 10° to 15°. The figure shows that the
COMPASS code noise on the B1 frequency is slightly larger than the GPS code noise on the L1 frequency whereas the COMPASS code observations on the B2 frequency have a significantly larger noise level than the GPS code observations on the L2 frequency. For both COMPASS and GPS, the noise level on the B1/L1 frequencies is smaller than that on the B2/L2 frequencies. It is noted that the STD value at the elevation angle of 32.5° is not available as there are no COMPASS observations at the elevation angles from 30° to 35°, as seen in Fig. 5. Fig. 5 illustrates the elevation angles of all visible COMPASS and GPS satellites at the station under open sky. During the entire test, the elevation angles of the GPS satellites vary from 10° to 90° whereas the COMPASS elevation angles change in a range of 20°–85°. Thus, the STD values of the multipath combinations with elevation angles below 20° and over 85° are unavailable for COMPASS in Fig. 4. Fig. 6 illustrates the STD of the multipath combinations for each COMPASS and GPS satellites. The noise level of the code observations on the B1/L1 frequencies is slightly smaller than that on the B2/L2 frequencies for all visible COMPASS and GPS satellites except the GPS satellites PRN 30 and PRN 11. The COMPASS satellite PRN 05 has a largest code noise level due to its low elevation angles. Shi et al. (2012) demonstrates that the GPS STDs vary in a range of 0.20–0.50 m while the COMPASS STDs are about 0.21–0.55 m using GPS/COMPASS receivers “UB240-CORS”. In terms of the variation ranges, the statistical values in Fig. 6 can match with their results well. But since observations were made at different locations with different receivers, the STD values for the same satellite are slightly different. The carrier-to-noise density ratio (C/N0) is defined as the ratio of the received carrier signal power to the received noise power, which indicates the quality of the received signal. The left plot of Fig. 7 depicts the mean values of C/N0 with respect to elevation angles with an increment of 5° for both GPS and COMPASS on two frequencies at the station under open sky. The C/N0 value is computed using the compressed signal strength value (i.e., 1–9) since the
Fig. 3. Multipath combinations on B1/L1 frequencies for all visible COMPASS and GPS satellites at the station under open sky.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
5
Table 1 STD of multipath combinations, cycle slip occurrence rate and data availability in six different observing conditions. MP1 (m) Open sky Trees Glass wall Water Signal tower High-voltage
MP2 (m)
Cycle-slips/observations (‰)
COM
GPS
COM
GPS
COM
GPS
COM
GPS
0.246 0.622 0.473 0.307 0.414 0.401
0.252 0.952 0.899 0.405 0.557 0.626
0.317 0.761 0.530 0.360 0.470 0.475
0.280 1.005 0.925 0.429 0.591 0.676
0.695 1.504 1.209 0.747 1.256 1.169
0.437 8.772 1.383 0.539 1.321 1.170
99 90 94 97 93 96
96 79 86 93 87 92
0.5
0.5
COM B2
0.4
GPS L1 GPS L2
0.3
Multipath (m)
COM B1
0.4
COMPASS
B1
B2
0.3 0.2 0.1 0 01
0.1
0 10
03
04
05
07
08
10
0.5
0.2 Multipath (m)
Multipath (m)
Data availability (%)
20
30
40 50 60 Elevation (degree)
70
80
90
0.4
GPS
L1
L2
0.3 0.2 0.1 0 01 03 06 07 08 11 13 14 16 19 20 23 30 31 32 Satellite PRN
Fig. 4. STD of multipath combinations over elevation angles for all visible COMPASS and GPS satellites on B1/L1 and B2/L2 frequencies at the station under open sky.
Fig. 6. STD of multipath combinations for each COMPASS and GPS satellites at the station under open sky.
original signal strength measurements are not available from the observation file. It can be seen that the C/N0 values on the COMPASS B1 frequency is slightly lower than that on the GPS L1 frequency whereas the C/N0 values on the COMPASS B2 frequency is significantly higher than that on the GPS L2 frequency at elevation angles of below 60°. To test the code multipath effect and the noise level in a poor satellite visibility condition, the multipath combination values are computed using the dataset collected under trees. Fig. 8 shows the multipath combinations for all
visible COMPASS and GPS satellites. In contrast to Fig. 3, the multipath combinations vary in a larger range for both COMPASS and GPS during the entire test. For COMPASS satellites, the STDs of the multipath combinations are 0.622 and 0.761 m on the B1 and B2 frequencies, respectively. Nevertheless, the STDs of the GPS multipath combinations are larger on both L1 and L2 frequencies. They are 0.952 and 1.005 m, respectively, as shown in Table 1. The COMPASS STD values are over two times larger than those obtained in the station under open sky while the GPS STD values are over three times larger. This
Fig. 5. Elevation angles for all visible COMPASS and GPS satellites at the station under open sky.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
6
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx Under trees
45
40
40
35
35
30 COM B1
25
COM B2
C/N0 (dB-Hz)
C/N0 (dB-Hz)
Under open sky
45
30 COM B1
25
COM B2
GPS L1
20 15 10
20
30
40 50 60 Elevation (degree)
70
80
GPS L1
20
GPS L2
90
15 10
GPS L2
20
30
40 50 60 Elevation (degree)
70
80
90
Fig. 7. Carrier-to-noise density ratios of the “SOUTH S82-C” receivers for GPS and COMPASS signals.
Fig. 8. Multipath combinations on B1/L1 frequencies for all visible COMPASS and GPS satellites at the station under trees.
suggests a significantly larger multipath effect and noise level caused by the diffraction and reflection of the satellite signals when they pass through the trees. The mean values of C/N0 at the station under trees are provided in the right plot of Fig. 7. Comparing with the left plot in Fig. 7, it is found that the C/N0 values for both GPS and COMPASS are slightly smaller than their corresponding
values in the open sky condition when the elevation angles are below 60°. Fig. 9 shows the cycle slip detection results for all observed GPS and COMPASS satellites at the station under trees. The identified cycle slip is marked with a small red circle. Different colors are adopted to distinguish signals at different satellite elevation angles. It is obvious that
Fig. 9. Cycle slip identification for all visible COMPASS and GPS satellites at the station under trees.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
the low elevation angle signals more easily suffer from cycle slips. Since most COMPASS satellites are observed in a relatively high elevation angles, its cycle slip occurrence rate is much lower than GPS in the limited satellite visibility condition. In addition to the larger multipath effect and noise level under the condition with limited satellite visibility, the cycle slip occurrence rates of 1.504‰ and 8.772‰ for COMPASS and GPS are much larger than those in the open sky condition which are 0.695‰ and 0.437‰, respectively, as provided in Table 1. Further, the data availability is also lower. Under the tree condition the data availability is 90% and 79% for COMPASS and GPS whereas they are 99% and 96% under the open sky condition, respectively. In terms of the cycle slip occurrence rate and the data availability, the COMPASS data outweigh GPS data because most COMPASS data are collected at relatively larger elevation angles.
3.2. Quality analysis of data collected under different multipath conditions In order to test the multipath effect, datasets were collected at the stations nearby a glass wall and a large area of water, respectively. Fig. 10 shows the multipath combinations on B1/L1 frequencies for all visible COMPASS and GPS satellites at the station nearby the glass wall. For COMPASS, the larger multipath combination values are mainly from satellite C07. Their maximum value exceeds 2 m during the GPS time of 5:30–7:20. The multipath combination values obtained from other COMPASS satellites mostly vary in a range of 1 m. By contrast, the GPS multipath combination values have a larger variation during the test period. Their maximum value even exceeds 4 m. The STD statistical values are 0.473 and 0.530 m for COMPASS and 0.899 and 0.925 m for GPS on two frequencies, respectively. It appears that more GPS observations undergo the multipath effect. This is because more GPS satellites are faced to the glass wall at low elevation angles
7
and thus their signals are partly reflected by the glass wall prior to reaching the receiver antenna. Another experiment was conducted nearby a calm lake, which easily reflects satellite signals and causes multipath effects. The multipath combinations on the B1/L1 frequencies for all visible COMPASS and GPS satellites are significantly smaller than those shown in Fig. 10. This is because that the modernized GNSS antenna is designed to mitigate the multipath effect by resisting the ground-reflected satellite signals. The STD statistical values are 0.307 and 0.360 m for COMPASS and 0.405 and 0.429 m for GPS on two frequencies, respectively. These values are slightly larger than those in the open sky condition, as seen in Table 1. 3.3. Quality analysis of data collected under different radio interference conditions In order to test the multipath effect in the radio interference conditions, experiments were carried out under a signal transmitting tower and high-voltage lines, respectively. Fig. 11 illustrates the multipath combinations on the B1/L1 frequencies for all visible COMPASS and GPS satellites at the station under a signal transmitting tower. In contrast to Fig. 3, it is clear that the radio interference indeed has an impact on the multipath combinations. The multipath combinations at the station under high-voltage lines are similar to those displayed in Fig. 11. Under the two radio interference conditions, the STD values of the multipath combinations are over 0.15 m larger for COMPASS and over 0.3 m larger for GPS on both frequencies than those under the open sky condition. The STD of multipath combinations, the cycle slip occurrence rate and the data availability in all six observing conditions have been provided in Table 1. It is noted that the “under trees” observing condition significantly increases the occurrence rate of cycle slips and decreases the data availability when compared with other observing conditions. In terms of multipath effect, cycle slips and data acquisition, the data quality in the station nearby a large
Fig. 10. Multipath combinations on B1/L1 frequencies for all visible COMPASS and GPS satellites at the station nearby a glass wall.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
8
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
Fig. 11. Multipath combinations on B1/L1 frequencies for all visible COMPASS and GPS satellites at the station under a signal transmitting tower.
area of water is the second best, following the data quality under the open sky condition. 4. Analysis on combined GPS/COMPASS single point positioning solutions As stated in the previous section, the pseudorange measurements are influenced by different magnitudes of multipath and noise under different observing conditions. In order to analyze their effects on SPP solutions, the same datasets collected in the six different observing conditions are used in post-mission to perform SPP in a combined GPS/COMPASS dual-system mode and a GPS-only single-system mode. The GPS PPP (Zumberge et al., 1997) solutions are used as coordinate references to assess the accuracy of the pseudorange-based SPP in the east, north and up directions. The P3 software package that is developed at the University of Calgary is used for the SPP and PPP processings. Since most SPP users are operating single-frequency receivers, only the pseudorange measurements on the B1/L1 frequencies are used. The ionospheric and tropospheric delay errors are corrected using the Klobuchar and Saastamoinen models, respectively. The satellite position and clock offset are computed using the broadcast ephemeris data. The COMPASS system adopts the Chinese Geodetic Coordinate System 2000 (CGCS2000) coordinate system, which is consistent with the International Terrestrial Reference Frame 1997 with a difference of about 3 cm (Shi et al., 2012). As a result, the difference between CGCS2000 and WGS-84 (GPS coordinate system) is only at a level of a few centimeters. Such a small difference in the coordinate references is negligible in our analysis of the pseudorange-based SPP performance. Thus, the coordinate transformation is not necessary in the combined GPS/ COMPASS SPP. In addition to the difference in the coordinate system, the COMPASS system has adopted an independent COMPASS Timing System (BDT), which differs from the UTC (Coordinated Universal Time) with a fractional second difference of smaller than 100 ns (CSNO, 2011). This accuracy is similar for the difference of GPS
Time and UTC (IS-GPS-200F, 2011). As a result, an additional unknown parameter is needed to estimate the system time difference between COMPASS and GPS along with the three coordinate components and one receiver clock offset in the combined GPS/COMPASS SPP. In order to analyze the positioning accuracy, the position coordinates at each epoch are independently estimated using the Least Squares method. In the combined GPS/COMPASS SPP, a crucial issue is how to set a proper weight between GPS and COMPASS pseudorange observations. For COMPASS, the residual satellite orbit and clock errors after using the broadcast ephemeris data are unclear so far. This will cause difficulty in assigning proper weights to GPS and COMPASS observations. In the implementation of the combined GPS/ COMPASS SPP, the initial variances of the GPS and COMPASS observations need to be provided to the Least Squares adjustment, which will be applied to determine the initial weight of the observations from two different GNSS systems. The actual variances will still take elevation angles into account and the weights assigned to observations are elevation dependent. Since there is no available reference regarding the setting of proper initial weights, we have used four different scenarios for initial weights, i.e., 1:1, 4:1, 9:1 and 16:1 (GPS versus COMPASS) in our performance analysis. The STDs of the GPS code observations are set to 0.3 m for all four scenarios while the STDs of the COMPASS code observations are set to 0.3, 0.6, 0.9 and 1.2 m, respectively. Table 2 lists the RMS (Root Mean Square) statistics of the positioning errors for the combined GPS/COMPASS Table 2 RMS statistics of positioning errors for combined GPS/COMPASS single point positioning using four different scenarios (m). Weights
East
North
Up
3-D
1:1 4:1 9:1 16:1
1.246 1.348 1.357 1.363
3.160 2.362 2.350 2.345
6.041 4.436 4.330 4.281
6.930 5.204 5.111 5.068
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
COM. Residual (m)
GPS Residual (m)
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx 6 3 0 -3 -6 6 3 0 -3 -6 3:30
4:30
5:30
6:30
GPS Time (HH:MM)
Fig. 12. GPS vs. COMPASS code observation residuals for the combined GPS/COMPASS SPP processing on B1/L1 frequencies.
Table 3 RMS statistics of GPS and COMPASS code residuals for combined GPS/ COMPASS single point positioning using four different scenarios (m). Weights
GPS residual
COMPASS residual
1:1 4:1 9:1 16:1
1.105 1.002 0.992 0.991
1.117 1.344 1.427 1.464
SPP processings based on the four different scenarios for initial weights using the dataset collected under the open sky condition. The RMS values suggest that an initial
9
weight of 1:1 between GPS and COMPASS is not proper since the three-dimensional positioning accuracy are significantly lower than the other three scenarios. When the initial weights of 4:1, 8:1 and 16:1 are used, there is no significant difference among the position solutions, which can also be seen from the RMS values. Since the improvement of the positioning accuracy is not significant when the initial weight is increased from 4:1 to 16:1, an initial weight of 4:1 between GPS and COMPASS is therefore adopted in the following data processing to avoid further decreasing the contribution of COMPASS observations to the positioning solution. Fig. 12 shows the GPS and COMPASS code observation residuals on the B1/L1 frequencies for the combined GPS/ COMPASS SPP processing in an initial weight setting of 4:1 using the dataset collected in the open sky condition. Different colors represent different satellites. It can be seen that most GPS residuals vary in a range of 2–2 m whereas most COMPASS residuals are in a wider range of 3–3 m. In contrast to GPS, the COMPASS residuals for each satellite remain fairly stable. This is because some tracked COMPASS satellites belong to GEO satellites whose elevation angles almost never change and the other COMPASS satellites are at relatively high elevation angles during the observation time, as seen in Fig. 5. The RMS statistical values of GPS and COMPASS residuals are listed in Table 3 with respect to the different initial weight settings. It can be seen that residual errors are increased in the COMPASS code observations and the residual errors in the GPS code observations are reduced when the initial weight changes from 1:1 to 4:1. As a result, the positioning accuracy is increased,
Under open sky
Under trees
East (m)
7 0
Up (m)
North (m)
-7 7
GP S GP S/COM
0 -7 20 0
Num. of sats.
PDOP
-20 4 2
15 5 3:30
4:30
5:30
6:30 3:30
4:30
5:30
6:30
GPS Time (HH:MM)
Fig. 13. GPS/COMPASS vs. GPS-only positioning errors of single point positioning in different satellite visibility conditions.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
10
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
Table 4 RMS statistical results of position errors in different observing conditions (m).
GPS-only
GPS/COM
East North Up 3-D East North Up 3-D
Open sky
Trees
Glass wall
Water
High-voltage
Signal tower
1.375 2.336 4.252 5.043 1.348 2.362 4.436 5.204
2.900 3.157 7.979 9.058 1.499 2.809 5.719 6.535
1.893 2.782 6.660 7.461 1.488 2.665 5.120 5.960
1.404 2.415 4.423 5.232 1.327 2.471 4.487 5.291
1.548 2.522 4.757 5.602 1.331 2.510 4.694 5.481
1.653 2.601 5.560 6.357 1.418 2.560 4.983 5.778
Under trees East (m)
7 0
Up (m)
North (m)
-7 7 0 -7 20
GPS GPS/COM
0
Num. of sats.
PDOP
-20 4 2
15 5 1:30
2:30
3:30
4:30 6:30
7:30
8:30
9:30
GPS Time (HH:MM)
Fig. 14. GPS/COMPASS vs. GPS-only positioning errors of single point positioning in the limited satellite visibility condition on October 23, 2012.
as shown in Table 2. When the initial weight is further increased, the variation in the GPS and COMPASS code residuals becomes very small. This indicates that the positioning accuracy cannot be further improved significantly. This explains again why an initial weight of 4:1 was adopted for the combined GPS/COMPASS SPP processings. Fig. 13 shows a comparison between the GPS/COMPASS and GPS-only position errors for SPP under different satellite visibility conditions. In the open sky condition, the average number of GPS satellites is 8.9. After adding 7 COMPASS satellites, the improvement on the satellite geometry is not significant. As a result, the combined GPS/COMPASS SPP does not improve the positioning accuracy over the GPS-only SPP. But for the station under trees, the positioning accuracy has been significantly improved by adding COMPASS data due to the improvement of the satellite geometry, especially over the period of 4:25–4:55. During this period, the maximum PDOP (Position Dilution of Precision) value reaches 6.1
due to a minimum of 5 satellites for GPS-only case but the maximum PDOP value is reduced to 3.0 after adding 6 COMPASS satellites. As a result, the largest positioning errors of 27.838, 13.659 and 52.326 m in the east, north and up directions are reduced to 5.884, 4.631 and 12.058 m after adding the COMPASS data. As most COMPASS satellites are tracked at high elevation angles, their signals are less blocked by the nearby trees. Table 4 lists the RMS statistical results of position errors at the stations under open sky and trees. In terms of three-dimensional position accuracy, the improvement is 28% at the station under trees. The COMPASS-only observations are used for SPP processing and RMS statistical results of positioning errors indicate an accuracy of 1.121, 3.928, and 8.011 m in the east, north, and up directions in the open sky condition, respectively. Comparing to GPS-only and GPS/COMPASS solutions, the COMPASS-only positioning accuracy is significantly lower, especially in the vertical component.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
The datasets collected in the multipath and radio interference conditions are also used for combined GPS/COMPASS and GPS-only SPP processings. Their RMS statistical results of position errors are also listed in Table 4. Table 4 indicates that the SPP positioning accuracy receives the biggest improvement from combining GPS and COMPASS for the station under trees where GPS satellite signals were partly blocked. The combined use of GPS and COMPASS increases the number of satellites and improves the satellite geometry. As a result, the positioning accuracy is improved. Comparing other RMS values with those in the open sky condition, it is found that the relatively poorer data quality in the multipath and radio interference conditions indeed has an impact on the positioning accuracy. To further validate the improvement that can bring by COMPASS data for positioning in the limited satellite visibility condition, an additional experiment was carried out in two sessions on October 23, 2012. The station is still located in an area of trees where the satellite signals are easily blocked by trees. Fig. 14 displays a comparison between the GPS/COMPASS and GPS-only position errors for SPP processing. Similar to the right plot of Fig. 13, the improvement on all three components are significant, especially for those epochs with large GPS-only positioning errors. The number of satellites and PDOP clearly demonstrate that the positioning accuracy improvement attributes to more visible satellites and improved satellite geometry. The RMS of GPS-only position errors indicates an accuracy of 2.723, 3.293 and 7.779 m in the east, north and up components while the corresponding RMS of GPS/COMPASS position errors are 1.683, 2.753 and 5.743 m, respectively. The improvement of the three-dimensional position accuracy reaches 26%, which is slightly lower than 28% as indicated in the right plot of Fig. 13. 5. Conclusions The COMPASS system presently consists of 13 operational satellites and has started to provide regional navigation services since December, 2011. We have tested its data quality and its positioning performance using two dualfrequency “SOUTH S82-C” GPS/COMPASS receivers to collect data under different observing conditions, namely, under open sky, under trees, nearby a glass wall, nearby a large area of water, under high-voltage lines and under a signal transmitting tower, respectively. All experiments are conducted in Changsha, China. In terms of the code multipath, cycle slip occurrence rate and data availability, the results with the test data have indicated better data quality for COMPASS in almost all observing conditions in comparison to GPS. This is primarily due to the fact that most COMPASS satellites are at relatively higher elevation angles. Further analysis over different elevation angles indicates that the COMPASS code noise on the B1 frequency has a comparable noise level to the GPS code observations on the L1 frequency whereas the B2 code observations have
11
a significantly larger noise level than the GPS L2 code observations. The same datasets under all six different observing conditions have been used to conduct combined GPS/COMPASS single point positioning (SPP). The result illustrates that the combined GPS/COMPASS SPP can significantly improve the positioning accuracy over the GPS-only SPP solutions under observing environments with signal attenuation. The results also nicely illustrate the impact of the multipath and radio interference on the accuracy of SPP solutions. Since the COMPASS system is still in an initial operational stage, all results are obtained based on a fairly limited amount of data. Acknowledgements The financial supports from NSFC (National Natural Science Foundation of China, No: 41004011) and Advanced Research Plan of Central South University (No: 2009QZZD002) are greatly appreciated. References Blewitt, G. An automatic editing algorithm for GPS data. Geophys. Res. Lett. 17 (3), 199–202, 1990. Cao, W., O’Keefe, K., Cannon, M.E. Evaluation of COMPASS ambiguity resolution performance using geometric-based techniques with comparison to GPS and Galileo, in: Proceedings of ION GNSS 2008, September 16–19, Savannah, Georgia, pp. 1688–1697, 2008. CSNO (China Satellite Navigation Office). BeiDou navigation satellite system signal in space interface control document (Test version), December 2011. CSNO (China Satellite Navigation Office). BeiDou navigation satellite system signal in space interface control document (open service signal B1I), Version 1.0, December 2012. Estey, L.H., Meertens, C.M. TEQC: the multi-purpose toolkit for GPS/ GLONASS data. GPS Solution 3 (1), 42–49, http://dx.doi.org/ 10.1007/PL00012778, 1999. Gao, G.X., Chen, A., Lo, S., De Lorenzo, D., Walter, T., Enge, P. Compass-M1 broadcast codes in E2, E5b, and E6 frequency bands. IEEE J. Sel. Top. Signal Process 3 (4), 599–612, http://dx.doi.org/ 10.1109/JSTSP.2009.2025635, 2009. Grelier, T., Ghion, A., Dantepal, J., Ries, L., Delatour, A., AvilaRodriguez, J.A., Wallner, S., Hein, G.W. COMPASS signal structure and first measurements, in: Proceedings of ION GNSS 2007, September 25–28, Fort Worth, Texas, pp. 3015–3024, 2007. Guo, H., He, H., Li, J., Wang, A. Estimation and mitigation of the main errors for centimetre-level Compass RTK solutions over medium-long baselines. J. Navig. 64, S113–S126, http://dx.doi.org/10.1017/ S0373463311000324, 2011. Hauschild, A., Montenbruck, O., Sleewaegen, J.M., Huisman, L., Teunissen, P.J.G. Characterization of COMPASS M-1 signals. GPS Solution 16 (1), 117–126, http://dx.doi.org/10.1007/s10291-011-02103, 2012. IS-GPS-200F. Global positioning system directorate systems engineering and integration interface specification, September 21, 2011. Li, X., Ge, M., Zhang, H., Nischan, T., Wickert, J. The GFZ real-time GNSS precise positioning service system and its adaption for COMPASS. Adv. Space Res. http://dx.doi.org/10.1016/j.asr.2012.06.025, 2012. Melbourne, W.G. The case for ranging in GPS based geodetic systems, in: Proceedings of the 1st international symposium on precise positioning with the global positioning system, Rockville, Maryland, pp. 373–386, 1985.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019
12
C. Cai et al. / Advances in Space Research xxx (2013) xxx–xxx
Montenbruck, O., Hauschild, A., Steigenberger, P., Hugentobler, U., Teunissen, P., Nakamura, S. Initial assessment of the COMPASS/ BeiDou-2 regional navigation satellite system. GPS Solution, http:// dx.doi.org/10.1007/s10291-012-0272-x, 2012. Shi, C., Zhao, Q., Hu, Z., Liu, J. Precise relative positioning using real tracking data from COMPASS GEO and IGSO satellites. GPS Solution, http://dx.doi.org/10.1007/s10291-012-0264-x, 2012. Wu¨bbena, G. Software developments for geodetic positioning with GPS using TI 4100 code and carrier measurements, in: Proceedings of the 1st international symposium on precise positioning with
the global positioning system, Rockville, Maryland, pp. 403–412, 1985. Zhang, S., Guo, J., Li, B., Rizos, C. An analysis of satellite visibility and relative positioning precision of COMPASS, in: Symposium for Chinese Professionals in GPS, Shanghai, China, August 18–20, pp. 41–46, 2010. Zumberge, J.F., Heflin, M.B., Jefferson, D.C., Watkins, M.M., Webb, F.H. Precise point positioning for the efficient and robust analysis of GPS data from large networks. J. Geophys. Res. 102 (B3), 5005–5017, http://dx.doi.org/10.1029/96JB03860, 1997.
Please cite this article in press as: Cai, C., et al. An analysis on combined GPS/COMPASS data quality and its effect on single point positioning accuracy under different observing conditions. J. Adv. Space Res. (2013), http://dx.doi.org/10.1016/j.asr.2013.02.019