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GPS orbit processing in support of low earth orbiter precise orbit determination
Available
Pergamon www.elsevier.com/Iocate/asr
online SCIENCE
at www.sciencedirect.com DIRECT.
doi: lO.l016/SO273-1177(03)00163-7
GPS ORBIT PROCESSING IN SUPPORT OF LOW EARTH ORBITER PRECISE ORBIT DETERMINATION I. Romero’, H. Boomkamp’, J. Dow’, C. Garcia’ ‘GMV at ESAIESOC, Robert-Bosch-Str. 5, Darmstadt, D-64293, Germany ‘European Space Operations Centre (ESOC), European Space Agency (ESA), Robert-Bosch-Str. 5, D-44293 Darmstadt, Germany
ABSTRACT There are currently an increasing number of LEO missions incorporating dual frequency GPS receivers for Satellite to Satellite Tracking. The majority of LEO precise orbit determination (POD) strategies rely on high quality GPS orbits and clocks such as those supplied by the IGS Final product. The availability of these products may not satisfy operational requirements due to their ten day latency. This paper studies the effect on the accuracy of the LEO POD of different kinds of GPS products as produced by ESOC, an IGS Analysis Centre. GPS products have been used for generating LEO POD results that differ in latency, frequency, and in being estimated or predicted. These results are then compared as part of the IGS LEO Pilot project to determine the improvement and degradation that can be expected by using the different GPS products. Additionally this paper will discuss an approach for the simultaneous solution of LEO and GPS POD. A simultaneous solution approach has the potential of providing improvements both in the GPS and in the LEO products, or to use fewer ground stations for generating the IGS products. In addition, it can reduce the latency that appears in the generation of LEO results based on separate GPS products. 0 2003 COSPAR. Published by Elsevier Science Ltd. All rights reserved. INTRODUCTION ESOC has been producing GPS precise orbits based on worldwide data from stations with geodetic GPS receivers for more than 10 years. As a member of the International GPS Service (formerly the International GPS Service for Geodynamics), IGS, since its inception in 1992, ESOC has been processing GPS data for precise orbit determination. Precise orbit determination is fundamental for ESOC, as the European Space Agency’s Operation Centre ESOC needs to have very accurate orbits to control and operate the spacecraft that ESA launches (i.e. Envisat, XMM, Cluster, etc). In the future the inclusion of GPS as a precise orbit determination method is a certainty in mission such as GOCE, and other future Low Earth Orbiter (LEO) missions. Therefore the accurate processing and estimation of orbits for the GPS constellation is fundamental for the POD of LEO. The different processing strategies, latencies, etc of the constellation POD need to be critically reviewed, to estimate what may be attainable with current state-of-the-art technology and the existing processes and products. These processing strategies and their differences are explained in this paper and an evaluation of their impact on the LEO POD is presented. GPS POD PROCESSING It is not the purpose of this section to explain exactly how the orbit determination process is carried out at ESOC. The processing is well documented in Dow et al. (2001), and Romero et al. (2002). A small summary will be given here, the main emphasis will be in the strategy followed to produce the different products submitted by ESOC as part of the IGS. Estimation Method Overview ESOC estimates precise GPS products using undifferenced pseudorange and carrier phase measurements at 5 minute intervals from dual frequency GPS geodetic quality receivers. The least squares batch estimator used at ESOC, BAHN, currently on version 7, is in continuous development for precise orbit determination. It can process most kinds of observations used for satellite orbit determination such as SLR (Satellite Laser Ranges), DORIS data, altimetry measurements, ranges, range-rates, plus the GNSS observables, pseudorange and carrier phase in doubleA& Space Res. Vol. 31, No. 8, pp. 1911-1916.2003 0 2003 COSPAR. Published by Elsevier Science Ltd. All rights Printed in Great Britain 0273-l 177/03 $30.00 + 0.00
reserved
1912
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et al.
differenced and undifferenced mode. The entire GPS product determination process runs within the ESOC GPSTracking and Data Analysis Facility (GPS-TDAF) which provides the framework for initialising inputs, running all the programs, organising the data, formatting the products and delivering them. The GPS-TDAF is largely an autonomous facility, which can run without human interaction for days, while it calculates and delivers the ESOC contributions to the IGS. Processing Strategies There are currently 3 GPS product lines open within the IGS, with 4 submissions: Final, Rapid and two daily Ultra-Rapid submissions. This section summari zes how ESOC calculates each of these products. Final and Ranid nroduct The daily processing in Final and Rapid modes proceed using very similar strategies, Figure 1 shows the RINEX data arc used when the solution for a particular day is calculated. A 4%hr arc of data is used to avoid the end-of-arc problems usual with batch estimation processes. The 12-hr overlap before and after the day calculated ensure good stability of the solution from day to day, plus complete observation arcs in the period of interest. I
day
1 day+1
1
Fig. 1. RINEX data arc and product content of ESOC Final and Rapid IGS processing.
The main difference between the two processes is the time at which the calculation actually takes place with respect to the day for which the GPS orbits are estimated. For the Rapid product the calculation for duy (Figure 1) takes place on day+1 and is submitted by 16:O0. The Final product containss the solution for day on up to day+7. This latency provides the Final product better stability due to the inclusion of more data, and better stations, if available. The Final product also benefits from the possibility of repeating a process in case of anomalous stations or satellites, which is not a realistic option for the Rapid product due to the short time available for processing. Ultra-Rapid The Ultra-Rapid orbits form the ‘most time-critical product. There are only three hours from the moment that the last observation is recorded by the receivers until the IGS publishes the combined product. The individual Analysis Centre solutions have to be ready 10 minutes before the combined product is published. It can take up to 45 minutes to receive a significant number of stations with measurements up to the end of the data arc, therefore the time window for the estimation process is limited to about 2 hours. The data arcs are as shown in Figure 2 and include 48 hours of GPS data plus either 24 or 48 hours of state vector observables at 15 minute intervals.
day-l
,
day +1
day +
t
day +2 I
Ultra-Rapid-00 sp3 contents
.
#
Ultra-Rapid-12 sp3 contents Fig. 2. RINEX data arc and product content of ESOC Ultra-Rapid IGS processing.
The arrows in Figure 2 show the approximate time at which processing starts during uiry+Z for both UltraRapid submissions. On days when there are very few stations available for processing it is useful to have the position observables from previous days to provide better results and better predictions.
GPS Orbit
Processing
in Support
of LEO
1913
GPS POD RESULTS Final Product Results These are the most accurate products, but sometimes a satellite may be excluded if it is affecting the overall estimation process in a negative way. This product benefits, as described above, from more available data and more processing time, with the possibiity of solution refinement. The 3D accuracy with respect to the IGS combined product can be seen in Figure 3 to be around 6 cm and 0.1 ns. The figure shows the daily weighted comparison of the ESOC solution versus the combination over the full GPS constellation over 24 hours, for 2001.
Fig. 3. ESOC Final product versus the IGS Final combined product.
Rapid Product Results The accuracy of the ESOC Rapid product, with respect to the IGS Rapid combined product, can be seen in Figure 4 to be around 8 cm and 0.1 ns. The figure shows the daily weighted comparison of the ESOC solution versus the combination over the full GPS constellation over 24 hours, for 2001.
Fig. 4. ESOC Rapid product versus the IGS Rapid combined product.
It is clear that the day-today variations of the ESOC Rapid solutions’ accuracy are greater than the accuracy of the ESOC Final products, even if the mean values are very similar. It is also worth pointing out that the ESOC Rapid product has no satellite exclusions, so if a very bad solution for a satellite is submitted it can distort the overall accuracy for that day even in a weighted RhB sense. It has the positive effect that at least there is a solution for all the satellites within the ESOC product. Ultra-Rapid Product Results The accuracy of the ESOC Ultra-Rapid product, with respect to the IGS combined product, can be seen in Figure 5 to be around 24 cm and 5 to 6 ns. The figure shows the daily weighted comparison of the ESOC solution versus the combination over the entire GPS constellation over 24&s, for all of 2001. Clock bias submissions started during 2001 and include 24hrs of estimated values and 24hrs of predicted values. Therefore the Ultra-Rapid product can be used in Real-Time applications that require more precision than what the GPS Navigation message can provide.
I. Romeroet
1914 I
I
-
I
I
al.
I ..__. ..-..._. _--_.._.._. .. .. .___.__.._. D m =
0
0 Orbit camp. (cm)
Fig. 5. ESOC Ultra-Rapid-00 product versus the IGS Ultra-Rapid combined product.
LEO POD PROCESSING The POD process for GPS LEO satellites (in particular, CHAMP) uses the same BAHN software as the IGS processing at ESOC, with some extensions to facilitate the processing of flight receiver data. This common basis supports the long-term objective of running simultaneous solutions for LEO satellites together with the GPS constellation. In the ESOC POD system, GPS-based POD for LEO satellites is still less stable than POD for the GPS constellation itself, and various consecutive processing steps are required. The present POD process for CHAMP is illustrated in Figure 6 and will be briefly explained. First, a kinematic POD solution is performed to obtain a reasonably accurate a priori orbit for CHAMP, based on fixed GPS orbits but estimating GPS clocks rather than interpolating them. This orbit is used to generate state vector observables that can be used in a dynamic POD solution. A substantial number of empirical parameters ensures that this solution follows the kinematic orbit, while removing its typical spikes and occasional divergences. In this solution the pseudorange data is also included, but at such a low weight that it does not yet influence the POD process itself. The ‘pseudorange residuals are only used to estimate the CHAMP clocks. In the next step the orbit parameters and CHAMP clocks from the a priori dynamic solution are used as initial values. The process still uses the state vector observables, but the pseudorange data is now included at a higher weight while the phase data is added at a very low weight. The main purpose of this solution is to detect and eliminate obviously inconsistent pairs of pseudorange and phase measurements, subscribed to incorrectly detected cycle slips. The normal GPS process at ESOC detects cycle slips in a pre-processing step before BAHN, but for the fast moving LEO receiver this algorithm is not always reliable. Finally, another dynamic POD process is run based on adequate a priori values for all dynamic parameters and LEO clocks, while only using reliable phase observations. This last process no longer includes the state vector observables, but still applies relatively strong constraints to the orbital parameters so that only minor adjustments of the a priori values will take place.
l l
l
PR + phase data Data quality determines orbit quality data Continuous required
OUTPUT: kinematic orbit
l
l
State observables from l State observables + PR kinematic orbit 0 Strong constraints on a Pseudorange data at priori parameters very low weight l Phase data at very low weight OUTPUT: LEO clocks
OUTPUT: phase data
l l
l
PR + phase data A priori parameters at medium constraints LEO clocks estimated OUTPUT: &al
orbit
Fig. 6. Four-step ESOC POD process for CHAMP
LEO POD RESULTS FOR DIFFERENT GPS REFERENCE PRODUCTS Using the POD sequence described above, CHAMP orbit solutions have been computed on the basis of the IGS final products, the ESOC final and rapid products, the estimated part of the ESOC ultra-rapid orbits and the predicted part of the ultra-rapid products. The analysed period covers the 1l-day CHAMP Orbit Campaign, see Boor& (2001), so that reliable external orbits are available as an independent check. Other outputs are the
GPS Orbit
Processing
in Support
1915
of LEO
tracking residuals for the GPS pseudorange and phase data, and SLR residuals were computed to the a posteriori orbits. For each of the five GPS re
120
100 60 =
60
-
40
---
20
0-f
I
,
-D-
ESOC
+ -X-
ESOC rapids ESOC UR est
1
!
finals
I
10 --__ 0,
!
140 141 142 143 144 145 146 147 146 149 150
I 140 141 142 143 144 145
I I < 7 146 147 146 149 150
DAY OF YEAR 2001
DAY OF YEAR 2001
Fig. 7. RMS of pseudorange
_
5-
I
Fig. 8. RMS of phase residuals
residuals
7
140
141
142
143
144
145
146
147
140
149
1% 1
DAY OF YEAR 2001
0 Fig. 9. RMS of SLR residuals
50
Orbit difference (cm)
Fig. 10 Orbit comparisons
As can be seen in the Table, the UR predicted case shows residuals that are much larger than the other four cases, and has been left out of the plots to maintain adequate vertical resolution. Table 1 also provides the 1l-day RMS of differences between the obtained CHAMP orbits and two external reference orbits, from DEOS (Ussel and Visser, 2002) and CSR. Figure 10 shows the orbit difference distributions. Each of the five test cases results in two curves, one for each external reference orbit. A single comparison curve between the reference orbits themselves is indicated as case A. From the tracking data residuals and the orbit comparisons with DEOS and CSR it is apparent that the CHAMP orbit precision levels obtained with the current POD set-up are still open for improvement. In particular, the small differences in the IGS finals, ESOC finals and ESOC rapids do not lead to notably different CHAMP results under
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these circumstances. Nonetheless this analysis is mainly comparative so that some useful information can be extracted from the available results. First, it is clear that for the UR predicted case the observed CHAMP orbit errors (- 110 cm RMS) are still of the same order of magnitude as the a priori orbit error in the GPS reference orbits and clocks. This suggests that even with relatively poor reference orbits and clocks the described CHAMP POD set-up runs in a stable way. The estimation of CHAMP clocks could be expected to suffer from poor reference clocks for GPS, but the way in which the process deals with this problem is by rejecting a higher percentage of the flight-receiver data (about 25% in case of ultra-rapid reference products, versus -15% in the other processes). In other words, the process manages to recognise poor a priori values for the GPS reference clocks as such. Comparing the pseudorange residuals (Fig. 7) with the residuals for phase (Fig. 8) and SLR (Fig. 9) shows that the UR case does not lead to significantly increased pseudorange residuals, even though the orbit error (indicated by the SLR residuals) and the phase residuals are higher. The explanation of this effect is probably that the increased CHAMP orbit error has been largely absorbed in the estimated LEO clocks. This effect could be reduced in case that more GPS satellites are tracked simultaneously (during the campaign period, CHAMP provided tracking to at most 8 GPS satellites simultaneously) or for LEO orbits that are higher (e.g. JASON). FUTURE DEVELOPMENTS As mentioned before, the current GPS-based approach for LEO POD is organ&d around the BAHN v. 7 software, which is not capable of running simultaneous POD processes for LEO and GPS. The main reasons for this are the limits to the number of parameters that can be estimated, and the long processing times that would be involved in the elaborate process from Fig. 6 if all GPS satellites would be included. The various modifications to BAHN for the CHAMP POD are at present being implemented in the ESOC NAPEOS software, which is also being upgraded for processing GPS data. In the near future both the IGS processing at ESOC and the LEO processing are expected to migrate to this new environment, removing many of the limits of the current system. The experience accumulated with CHAMP has lead to the idea that the clocks and ambiguities should ideally be solved together, even together with the orbits themselves. This leads to a large number (> 104) of epoch-dependent parameters, resulting in a large but very sparse normal matrix. A separate least squares estimator will be implemented in the NAPEOS software to cope with this particular matrix structure. The resulting POD package is expected to allow simultaneous solutions for the full GPS constellation in combination with various LEO satellites. CONCLUSIONS Availability of high quality GPS orbits is fundamental for accurate LEO POD based on GPS data. Although the current LEO POD system at ESOC has known shortcomings that limit CHAMP orbit precision to about 20 cm RMS, the analysis shows that the quality of a priori GPS orbits and clocks is also reflected in the LEO orbits. In an operational environment where only a few hours are available for LEO POD, predicted GPS orbits and clocks may have to be used from the Ultra-Rapid product. The LEO orbit precision that could at present be reached in this case is about 120 cm RMS. Future developments at ESOC are aimed at estimating LEO orbits and clocks simultaneously with the orbits and clocks of the full GPS constellation. REFERENCES Boor&, H.J., CHAMP Orbit Campaign webpages, http://nng.esoc.esa.de/gps/campaign.html Dow, J.M., J. Feltens, C. Garcia, and I. Romero, The ESA/ESOC IGS Analysis Centre, Annual Report 2000, lntemational GPS Service 2000 Technical Report, JPL Publication 02-012, IGS Central Bureau eds., Jet Propulsion Laboratory, Pasadena, CA, 200 1. Romero. K., C. Garcia, R. Kahle, J. Dow, and T. Martin-Mur, Precise Orbits Determination of GLONASS Satellites at the European Space Agency, Adv. Space Res., 30 (2), 281-287,2002. van den Ijssel, J., and P. Visser, DEOS CHAMP precise orbit determination, Adv. Space Res., this issue, 2003. E-mail address of H. Boon&am: [email protected] Manuscript received 19 October 2002, Revised 7 December 2002, Accepted 12 March 2003.
Pergamon www.elsevier.com/Iocate/asr
online SCIENCE
at www.sciencedirect.com DIRECT.
doi: lO.l016/SO273-1177(03)00163-7
GPS ORBIT PROCESSING IN SUPPORT OF LOW EARTH ORBITER PRECISE ORBIT DETERMINATION I. Romero’, H. Boomkamp’, J. Dow’, C. Garcia’ ‘GMV at ESAIESOC, Robert-Bosch-Str. 5, Darmstadt, D-64293, Germany ‘European Space Operations Centre (ESOC), European Space Agency (ESA), Robert-Bosch-Str. 5, D-44293 Darmstadt, Germany
ABSTRACT There are currently an increasing number of LEO missions incorporating dual frequency GPS receivers for Satellite to Satellite Tracking. The majority of LEO precise orbit determination (POD) strategies rely on high quality GPS orbits and clocks such as those supplied by the IGS Final product. The availability of these products may not satisfy operational requirements due to their ten day latency. This paper studies the effect on the accuracy of the LEO POD of different kinds of GPS products as produced by ESOC, an IGS Analysis Centre. GPS products have been used for generating LEO POD results that differ in latency, frequency, and in being estimated or predicted. These results are then compared as part of the IGS LEO Pilot project to determine the improvement and degradation that can be expected by using the different GPS products. Additionally this paper will discuss an approach for the simultaneous solution of LEO and GPS POD. A simultaneous solution approach has the potential of providing improvements both in the GPS and in the LEO products, or to use fewer ground stations for generating the IGS products. In addition, it can reduce the latency that appears in the generation of LEO results based on separate GPS products. 0 2003 COSPAR. Published by Elsevier Science Ltd. All rights reserved. INTRODUCTION ESOC has been producing GPS precise orbits based on worldwide data from stations with geodetic GPS receivers for more than 10 years. As a member of the International GPS Service (formerly the International GPS Service for Geodynamics), IGS, since its inception in 1992, ESOC has been processing GPS data for precise orbit determination. Precise orbit determination is fundamental for ESOC, as the European Space Agency’s Operation Centre ESOC needs to have very accurate orbits to control and operate the spacecraft that ESA launches (i.e. Envisat, XMM, Cluster, etc). In the future the inclusion of GPS as a precise orbit determination method is a certainty in mission such as GOCE, and other future Low Earth Orbiter (LEO) missions. Therefore the accurate processing and estimation of orbits for the GPS constellation is fundamental for the POD of LEO. The different processing strategies, latencies, etc of the constellation POD need to be critically reviewed, to estimate what may be attainable with current state-of-the-art technology and the existing processes and products. These processing strategies and their differences are explained in this paper and an evaluation of their impact on the LEO POD is presented. GPS POD PROCESSING It is not the purpose of this section to explain exactly how the orbit determination process is carried out at ESOC. The processing is well documented in Dow et al. (2001), and Romero et al. (2002). A small summary will be given here, the main emphasis will be in the strategy followed to produce the different products submitted by ESOC as part of the IGS. Estimation Method Overview ESOC estimates precise GPS products using undifferenced pseudorange and carrier phase measurements at 5 minute intervals from dual frequency GPS geodetic quality receivers. The least squares batch estimator used at ESOC, BAHN, currently on version 7, is in continuous development for precise orbit determination. It can process most kinds of observations used for satellite orbit determination such as SLR (Satellite Laser Ranges), DORIS data, altimetry measurements, ranges, range-rates, plus the GNSS observables, pseudorange and carrier phase in doubleA& Space Res. Vol. 31, No. 8, pp. 1911-1916.2003 0 2003 COSPAR. Published by Elsevier Science Ltd. All rights Printed in Great Britain 0273-l 177/03 $30.00 + 0.00
reserved
1912
I. Romero
et al.
differenced and undifferenced mode. The entire GPS product determination process runs within the ESOC GPSTracking and Data Analysis Facility (GPS-TDAF) which provides the framework for initialising inputs, running all the programs, organising the data, formatting the products and delivering them. The GPS-TDAF is largely an autonomous facility, which can run without human interaction for days, while it calculates and delivers the ESOC contributions to the IGS. Processing Strategies There are currently 3 GPS product lines open within the IGS, with 4 submissions: Final, Rapid and two daily Ultra-Rapid submissions. This section summari zes how ESOC calculates each of these products. Final and Ranid nroduct The daily processing in Final and Rapid modes proceed using very similar strategies, Figure 1 shows the RINEX data arc used when the solution for a particular day is calculated. A 4%hr arc of data is used to avoid the end-of-arc problems usual with batch estimation processes. The 12-hr overlap before and after the day calculated ensure good stability of the solution from day to day, plus complete observation arcs in the period of interest. I
day
1 day+1
1
Fig. 1. RINEX data arc and product content of ESOC Final and Rapid IGS processing.
The main difference between the two processes is the time at which the calculation actually takes place with respect to the day for which the GPS orbits are estimated. For the Rapid product the calculation for duy (Figure 1) takes place on day+1 and is submitted by 16:O0. The Final product containss the solution for day on up to day+7. This latency provides the Final product better stability due to the inclusion of more data, and better stations, if available. The Final product also benefits from the possibility of repeating a process in case of anomalous stations or satellites, which is not a realistic option for the Rapid product due to the short time available for processing. Ultra-Rapid The Ultra-Rapid orbits form the ‘most time-critical product. There are only three hours from the moment that the last observation is recorded by the receivers until the IGS publishes the combined product. The individual Analysis Centre solutions have to be ready 10 minutes before the combined product is published. It can take up to 45 minutes to receive a significant number of stations with measurements up to the end of the data arc, therefore the time window for the estimation process is limited to about 2 hours. The data arcs are as shown in Figure 2 and include 48 hours of GPS data plus either 24 or 48 hours of state vector observables at 15 minute intervals.
day-l
,
day +1
day +
t
day +2 I
Ultra-Rapid-00 sp3 contents
.
#
Ultra-Rapid-12 sp3 contents Fig. 2. RINEX data arc and product content of ESOC Ultra-Rapid IGS processing.
The arrows in Figure 2 show the approximate time at which processing starts during uiry+Z for both UltraRapid submissions. On days when there are very few stations available for processing it is useful to have the position observables from previous days to provide better results and better predictions.
GPS Orbit
Processing
in Support
of LEO
1913
GPS POD RESULTS Final Product Results These are the most accurate products, but sometimes a satellite may be excluded if it is affecting the overall estimation process in a negative way. This product benefits, as described above, from more available data and more processing time, with the possibiity of solution refinement. The 3D accuracy with respect to the IGS combined product can be seen in Figure 3 to be around 6 cm and 0.1 ns. The figure shows the daily weighted comparison of the ESOC solution versus the combination over the full GPS constellation over 24 hours, for 2001.
Fig. 3. ESOC Final product versus the IGS Final combined product.
Rapid Product Results The accuracy of the ESOC Rapid product, with respect to the IGS Rapid combined product, can be seen in Figure 4 to be around 8 cm and 0.1 ns. The figure shows the daily weighted comparison of the ESOC solution versus the combination over the full GPS constellation over 24 hours, for 2001.
Fig. 4. ESOC Rapid product versus the IGS Rapid combined product.
It is clear that the day-today variations of the ESOC Rapid solutions’ accuracy are greater than the accuracy of the ESOC Final products, even if the mean values are very similar. It is also worth pointing out that the ESOC Rapid product has no satellite exclusions, so if a very bad solution for a satellite is submitted it can distort the overall accuracy for that day even in a weighted RhB sense. It has the positive effect that at least there is a solution for all the satellites within the ESOC product. Ultra-Rapid Product Results The accuracy of the ESOC Ultra-Rapid product, with respect to the IGS combined product, can be seen in Figure 5 to be around 24 cm and 5 to 6 ns. The figure shows the daily weighted comparison of the ESOC solution versus the combination over the entire GPS constellation over 24&s, for all of 2001. Clock bias submissions started during 2001 and include 24hrs of estimated values and 24hrs of predicted values. Therefore the Ultra-Rapid product can be used in Real-Time applications that require more precision than what the GPS Navigation message can provide.
I. Romeroet
1914 I
I
-
I
I
al.
I ..__. ..-..._. _--_.._.._. .. .. .___.__.._. D m =
0
0 Orbit camp. (cm)
Fig. 5. ESOC Ultra-Rapid-00 product versus the IGS Ultra-Rapid combined product.
LEO POD PROCESSING The POD process for GPS LEO satellites (in particular, CHAMP) uses the same BAHN software as the IGS processing at ESOC, with some extensions to facilitate the processing of flight receiver data. This common basis supports the long-term objective of running simultaneous solutions for LEO satellites together with the GPS constellation. In the ESOC POD system, GPS-based POD for LEO satellites is still less stable than POD for the GPS constellation itself, and various consecutive processing steps are required. The present POD process for CHAMP is illustrated in Figure 6 and will be briefly explained. First, a kinematic POD solution is performed to obtain a reasonably accurate a priori orbit for CHAMP, based on fixed GPS orbits but estimating GPS clocks rather than interpolating them. This orbit is used to generate state vector observables that can be used in a dynamic POD solution. A substantial number of empirical parameters ensures that this solution follows the kinematic orbit, while removing its typical spikes and occasional divergences. In this solution the pseudorange data is also included, but at such a low weight that it does not yet influence the POD process itself. The ‘pseudorange residuals are only used to estimate the CHAMP clocks. In the next step the orbit parameters and CHAMP clocks from the a priori dynamic solution are used as initial values. The process still uses the state vector observables, but the pseudorange data is now included at a higher weight while the phase data is added at a very low weight. The main purpose of this solution is to detect and eliminate obviously inconsistent pairs of pseudorange and phase measurements, subscribed to incorrectly detected cycle slips. The normal GPS process at ESOC detects cycle slips in a pre-processing step before BAHN, but for the fast moving LEO receiver this algorithm is not always reliable. Finally, another dynamic POD process is run based on adequate a priori values for all dynamic parameters and LEO clocks, while only using reliable phase observations. This last process no longer includes the state vector observables, but still applies relatively strong constraints to the orbital parameters so that only minor adjustments of the a priori values will take place.
l l
l
PR + phase data Data quality determines orbit quality data Continuous required
OUTPUT: kinematic orbit
l
l
State observables from l State observables + PR kinematic orbit 0 Strong constraints on a Pseudorange data at priori parameters very low weight l Phase data at very low weight OUTPUT: LEO clocks
OUTPUT: phase data
l l
l
PR + phase data A priori parameters at medium constraints LEO clocks estimated OUTPUT: &al
orbit
Fig. 6. Four-step ESOC POD process for CHAMP
LEO POD RESULTS FOR DIFFERENT GPS REFERENCE PRODUCTS Using the POD sequence described above, CHAMP orbit solutions have been computed on the basis of the IGS final products, the ESOC final and rapid products, the estimated part of the ESOC ultra-rapid orbits and the predicted part of the ultra-rapid products. The analysed period covers the 1l-day CHAMP Orbit Campaign, see Boor& (2001), so that reliable external orbits are available as an independent check. Other outputs are the
GPS Orbit
Processing
in Support
1915
of LEO
tracking residuals for the GPS pseudorange and phase data, and SLR residuals were computed to the a posteriori orbits. For each of the five GPS re
120
100 60 =
60
-
40
---
20
0-f
I
,
-D-
ESOC
+ -X-
ESOC rapids ESOC UR est
1
!
finals
I
10 --__ 0,
!
140 141 142 143 144 145 146 147 146 149 150
I 140 141 142 143 144 145
I I < 7 146 147 146 149 150
DAY OF YEAR 2001
DAY OF YEAR 2001
Fig. 7. RMS of pseudorange
_
5-
I
Fig. 8. RMS of phase residuals
residuals
7
140
141
142
143
144
145
146
147
140
149
1% 1
DAY OF YEAR 2001
0 Fig. 9. RMS of SLR residuals
50
Orbit difference (cm)
Fig. 10 Orbit comparisons
As can be seen in the Table, the UR predicted case shows residuals that are much larger than the other four cases, and has been left out of the plots to maintain adequate vertical resolution. Table 1 also provides the 1l-day RMS of differences between the obtained CHAMP orbits and two external reference orbits, from DEOS (Ussel and Visser, 2002) and CSR. Figure 10 shows the orbit difference distributions. Each of the five test cases results in two curves, one for each external reference orbit. A single comparison curve between the reference orbits themselves is indicated as case A. From the tracking data residuals and the orbit comparisons with DEOS and CSR it is apparent that the CHAMP orbit precision levels obtained with the current POD set-up are still open for improvement. In particular, the small differences in the IGS finals, ESOC finals and ESOC rapids do not lead to notably different CHAMP results under
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these circumstances. Nonetheless this analysis is mainly comparative so that some useful information can be extracted from the available results. First, it is clear that for the UR predicted case the observed CHAMP orbit errors (- 110 cm RMS) are still of the same order of magnitude as the a priori orbit error in the GPS reference orbits and clocks. This suggests that even with relatively poor reference orbits and clocks the described CHAMP POD set-up runs in a stable way. The estimation of CHAMP clocks could be expected to suffer from poor reference clocks for GPS, but the way in which the process deals with this problem is by rejecting a higher percentage of the flight-receiver data (about 25% in case of ultra-rapid reference products, versus -15% in the other processes). In other words, the process manages to recognise poor a priori values for the GPS reference clocks as such. Comparing the pseudorange residuals (Fig. 7) with the residuals for phase (Fig. 8) and SLR (Fig. 9) shows that the UR case does not lead to significantly increased pseudorange residuals, even though the orbit error (indicated by the SLR residuals) and the phase residuals are higher. The explanation of this effect is probably that the increased CHAMP orbit error has been largely absorbed in the estimated LEO clocks. This effect could be reduced in case that more GPS satellites are tracked simultaneously (during the campaign period, CHAMP provided tracking to at most 8 GPS satellites simultaneously) or for LEO orbits that are higher (e.g. JASON). FUTURE DEVELOPMENTS As mentioned before, the current GPS-based approach for LEO POD is organ&d around the BAHN v. 7 software, which is not capable of running simultaneous POD processes for LEO and GPS. The main reasons for this are the limits to the number of parameters that can be estimated, and the long processing times that would be involved in the elaborate process from Fig. 6 if all GPS satellites would be included. The various modifications to BAHN for the CHAMP POD are at present being implemented in the ESOC NAPEOS software, which is also being upgraded for processing GPS data. In the near future both the IGS processing at ESOC and the LEO processing are expected to migrate to this new environment, removing many of the limits of the current system. The experience accumulated with CHAMP has lead to the idea that the clocks and ambiguities should ideally be solved together, even together with the orbits themselves. This leads to a large number (> 104) of epoch-dependent parameters, resulting in a large but very sparse normal matrix. A separate least squares estimator will be implemented in the NAPEOS software to cope with this particular matrix structure. The resulting POD package is expected to allow simultaneous solutions for the full GPS constellation in combination with various LEO satellites. CONCLUSIONS Availability of high quality GPS orbits is fundamental for accurate LEO POD based on GPS data. Although the current LEO POD system at ESOC has known shortcomings that limit CHAMP orbit precision to about 20 cm RMS, the analysis shows that the quality of a priori GPS orbits and clocks is also reflected in the LEO orbits. In an operational environment where only a few hours are available for LEO POD, predicted GPS orbits and clocks may have to be used from the Ultra-Rapid product. The LEO orbit precision that could at present be reached in this case is about 120 cm RMS. Future developments at ESOC are aimed at estimating LEO orbits and clocks simultaneously with the orbits and clocks of the full GPS constellation. REFERENCES Boor&, H.J., CHAMP Orbit Campaign webpages, http://nng.esoc.esa.de/gps/campaign.html Dow, J.M., J. Feltens, C. Garcia, and I. Romero, The ESA/ESOC IGS Analysis Centre, Annual Report 2000, lntemational GPS Service 2000 Technical Report, JPL Publication 02-012, IGS Central Bureau eds., Jet Propulsion Laboratory, Pasadena, CA, 200 1. Romero. K., C. Garcia, R. Kahle, J. Dow, and T. Martin-Mur, Precise Orbits Determination of GLONASS Satellites at the European Space Agency, Adv. Space Res., 30 (2), 281-287,2002. van den Ijssel, J., and P. Visser, DEOS CHAMP precise orbit determination, Adv. Space Res., this issue, 2003. E-mail address of H. Boon&am: [email protected] Manuscript received 19 October 2002, Revised 7 December 2002, Accepted 12 March 2003.