JASON-2 NEAR REAL TIME PRECISE ORBIT DETERMINATION BASED ON GRAS GSN

Yago Andrés (1), Pier Luigi Righetti (2), Anders Soerensen (2)

(1) Edymac at EUMETSAT, Eumetsat Allee 1, D-64295 Darmstadt, Germany, +49(0)6151-807 665, [email protected] (2) EUMETSAT, Eumetsat Allee 1, D-64295 Darmstadt, Germany, +49(0)6151-807 776, [email protected] +49(0)6151-807-353, [email protected]

ABSTRACT

EUMETSAT computes operationally the Near-Real-Time (NRT) precise orbit of MetOp-A satellite using both the data provided by the GRAS (GNSS Receiver for Atmospheric Sounding) instrument and support data provided by the GRAS Ground Support Network (GSN).

The GSN system, operated by ESA´s European Space Operations Centre (ESOC), provides in near real time a set of precise GPS products (satellite ephemerides and high frequency clock corrections) as well as other auxiliary data (i.e. Earth Orientation Parameters). These products are subjected to very stringent requirements in accuracy, timeliness and reliability, to ensure the required service to the meteorological community (99 % within 3 hours).

The experience acquired in the nearly three years of operations of MetOp-A has been applied to the OSTM/Jason-2 mission. EUMETSAT is in charge of distributing the Operational Geophysical Data Records (OGDR) to the European users. The OGDR is a new, real-time operational product specially developed for the Jason-2 mission. The OGDR is the faster product delivered to the users, with a short delay of 3 - 5 hours, and a specified radial orbit accuracy of 10cm RMS. The product takes advantage of the precise orbit computed on-board by the Doppler Orbitography and Radio-positioning Integrated by Satellite (DORIS) navigator DIODE (Détermination Immédiate d'Orbite par DORIS Embarqué).

Both missions present comparable specifications for the NRT precise orbit determination (POD) (10cm radial RMS), being the computation methods completely different. While the OSTM/Jason-2 missions uses the orbits computed on-board by the DIODE, the Metop-A mission computes the orbit on-ground in NRT based on both GPS data from an on-board receiver and on GPS precise ephemerides delivered by the GRAS GSN system.

The method for computing the NRT precise orbit for the GRAS instrument can be fully applied to the OSTM/Jason-2 mission. Metop-A experience shows that the accuracy of the GPS based computed orbit on-ground can usually achieve in NRT a better accuracy than the on-board solution, but having a greater complexity due to the processing needed on-ground.

The purpose of this paper is to present the system architecture set up at EUMETSAT for running in near-real-time an experimental POD process of the Jason-2 satellite and to show that the achieved accuracy is comparable to that of the official OGDR product, with similar latency. Afterwards some ways of improving the precision of the POD are presented; these are mainly the use of more accurate NRT GPS auxiliary data, better models and the use in near real time of quaternions instead of the nominal attitude law.

1. OSTM/JASON-2 MISSION The Ocean Surface Topography Mission (OSTM) is a joint effort by four organizations to measure sea surface height by using a radar altimeter mounted on a low-earth orbiting satellite called Jason-2. The four mission participants are: • National Oceanic and Atmospheric Administration (NOAA) • National Aeronautics and Space Administration (NASA) • France’s Centre National d’Etudes Spatiales (CNES) • European Meteorological Satellite Organisation (EUMETSAT)

Jason-2 is 3 metres high and weighted about 500 kilos at launch, with 580 watts of power. It is a 3-axis stabilised satellite; nadir pointing is maintained by reaction wheels and magnetic torque rods. A hydrazine propellant system provides orbital maintenance. Jason-2 has a designed lifetime of about 5 years. It has been placed into the same low earth, non-sun-synchronous orbit as Jason-1, at an altitude of 1336 kilometres, inclined 66 degrees, to provide virtually complete coverage of ice-free oceans. With a global data coverage between 66°N and 66°S latitude and a 10-day repeat of the ground track (±1-km accuracy), Jason-2 provides coverage of 95% of ice-free oceans every 10 days.

The OSTM is built around a series of 'Jason' satellites (named after the mythical Greek mariner) which will collect global ocean surface data on a continuous basis for several decades. The aim is to measure the global sea surface height to an accuracy of a few centimetres every 10 days, to determine ocean circulation and mean sea level trend in support of weather forecasting, climate monitoring and operational oceanography. Launched on 20 June 2008, Jason-2 overlaps with the Jason-1 mission to secure the continuity of high accuracy satellite altimetry observations. Jason-2 continues the high- accuracy altimetric data collection done by the Topex/Poseidon and Jason-1 satellites and provides a transition into operational satellite altimetry; it is an essential component of the global ocean-observing systems.

Three location systems (See Fig. 1) provided by three different payloads combine to measure the satellite's precise position in orbit to within a few centimetres on the radial component:

• Doppler Orbitography and Radio-positioning Integrated by Satellite (DORIS) receiver provided by CNES. • Global Positioning System Payload (GPSP) receiver provided by NASA • Laser Retroreflector Array (LRA) provided by NASA.

Three different data products are produced and distributed to the users: • The Operational Geophysical Data Record (OGDR) with a latency of 3-5 hours • The Interim Geophysical Data Record (IGDR) with a latency of 1 -2 days • The Geophysical Data Record (GDR) with a specified latency smaller than 60 days

The Geophysical Data Record (GDR) provides fully-validated data produced usually within five to six weeks of the events being recorded and covers sea surface height, principally for climate monitoring and climate modelling. The main users of this product are within the climate research community, for climate model verifications, for routine sea level station validation, and for the International Panel for Climate Change Assessment Report on rising sea levels. The orbits used for generating these products are generated by CNES and are called POE (Precise Orbit Ephemeris). They are computed using all three location systems: DORIS, LASER and GPS. They have an RMS orbit accuracy specification of 1.5 cm in the radial direction.

Fig. 1. Jason-2 measurement system (courtesy of CNES)

The Interim Geophysical Data Record (IGDR) provides sea surface data which is produced within 1- 1.5 days of being recorded. This record includes analysed data on sea surface height, absolute dynamic topography and ocean geostrophic velocities for medium-range weather forecasting, seasonal forecasting and ocean weather applications. These products are generated using the orbits called MOE (Medium-accuracy Orbit Ephemeris) and computed by CNES using DORIS + LASER data. They have an RMS orbit accuracy specification of 2.5 cm in the radial direction.

Finally, the Operational Geophysical Data Record (OGDR) is a new, real-time operational product specially developed for the Jason-2 mission. The OGDR is the fastest product delivered to the users, with a short delay of 3 - 5 hours. This product is essentially dedicated to marine meteorology applications. The primary purpose is to provide in near real-time data to meteorological organisations carrying out nowcasting and operational wave forecasting, but it also makes data on sea surface height anomalies available for ocean users.

The OGDR is processed at the EUMETSAT and NOAA ground centres and disseminated over the EUMETCast satellite broadcasting system as well as via data networks and the NOAA Global Telecommunication System network. Key user organisations include European Centre for Medium- Range Weather Forecasts (ECMWF), Météo-France, National Oceanic and Atmospheric Administration (NOAA), UK Met Office and the Norwegian Meteorological Institute. The orbits used for generating these products are computed on-board by the DORIS DIODE Navigator, and have an RMS orbit accuracy specification of 10cm in the radial direction. 2. GRAS-GSN SYSTEM The GRAS GSN System is an operational system designed and operated by ESA´s European Space Operation Centre (ESOC) to deliver supporting data to the Metop Core Ground Segment (CGS) in order to process atmospheric sounding data delivered by the Metop GRAS instrument and for Metop precise orbit determination [1].

The system is subjected to very stringent requirements in availability (99% asymptotic availability), reliability (6 hours maximal interruption, less than 3 interruptions of service per 30 days period) and accuracy (1m for position and 1ns for clock bias, both 2-sigma).

The support data consists of: • GPS orbit predictions and clock bias estimation. GPS orbits are updated every 3 hours, while GPS clock bias estimations every 15minutes. • Ground tracking data of all GPS occulting spacecrafts by GPS receivers globally distributed • Auxiliary files (i.e. Earth Orientation Parameters)

The GRAS GSN can be divided into 2 main blocks: • GPS receiver station network; operated by different providers (i.e. NRCan, GFZ, FS and ESOC), collecting GPS and meteorological data and transferring the information in Near Real Time to the GRAS GSN Processing Centre. • The GRAS GSN Processing Centre (GRAS GSNPC); in charge of monitoring, processing, formatting, archiving and distributing the products to the Metop CGS.

The GSN receiver station network consists of a set of approximately 40 redundant stations (25 primary and 15 back-up, which are geographically distributed (See Fig. 2). RINEX files of 15 minutes at 1Hz frequency are continuously provided by at least 25 stations with a latency of less than 5 minutes.

Fig. 2. Primary GSN Stations (courtesy of ESA/ESOC)

The GSN Processing Centre is operated from ESOC´s Navigation Facility, located in Darmstadt. It has its hardware divided into two independent chains for redundancy. The relevant products for POD computed by the GSN PC are: • NRT GPS orbits, including 36h of prediction with an update frequency of 3 hours • NRT GPS estimated clock corrections at 1Hz; update frequency of 15min and available 1 hour after sensing time • NRT Earth Orientation parameters resulting from the same least square estimation process as the GPS orbits

3. NRT JASON-2 POD SYSTEM BASED ON GRAS-GSN Using the in-house available GRAS GSN service and the NRT Jason-2 GPS data from the GPSP available through the Jason-2 Ground Segment (J2GS), EUMETSAT has setup a NRT Jason-2 POD system. The architecture of the system is depicted in Fig.3; please note that each processing unit is connected to the database and to the archive, but that is not shown in the diagram for clarity. For the implementation of the architecture the S4P [2] of NASA is used as an automated data driven processor.

JASON-2 GS Data: GSN Products RINEX, Predicted Orbit, Auxiliary Data (GPS Orbits, Clocks, OGDR, MOE, POE (Solar activity)

FileManager

Update GSN Process Predicted Process RINEX Process Aux-Data Process OGDR_MOE_POE

Latest Latest Latest Latest GSN Products Predicted Orbit RINEX Auxiliary Data

LEO_POD Data Cleaning Database Reference LSQ Estimation Orbits (SP3)

Post Processing / Validation Archive

JASON-2 NRT Precise Orbit

Fig. 3. NRT POD Architecture

Every processing unit is implemented as a station in S4P, and each station is communicating with the following one(s) with workorders containing the file(s) to be processed. Each file processed by any station is saved in a database with following fields: file name, file generation time, processing unit, processing start time. In this way the timeliness of the system can be monitored. The FileManager process, is started on a regular basis, and checks if new files from the J2GS have arrived, if there are any new GSN auxiliary files in its ftp server, or if there is any other auxiliary file. Depending on the availability of new file(s), one or more workorders are generated with the new file(s) and passed to the relevant processing unit.

In case of a new file in the GSN system, the station ‘Update GSN’ is started, which is updating the ‘latest GSN products’ available for the system. Old files are archived for a period, and deleted afterwards.

In case of a new predicted orbit or a new attitude file from the J2GS arrives, the corresponding station is started, updating the attitude file or the predicted J2 orbit. If a new J2 data product (OGDR, IGDR or GDR) arrives, its orbital information is converted to the standard SP3 format, and saved for validation/comparison purposes.

Finally, whenever a new RINEX file arrives (usually every orbit i.e. 2 hours, except in case of blind orbits) it is processed by the ‘Process RINEX’ station: decimated to 30 seconds, saved in the file system and passed over to the LEO_POD station.

The LEO_POD station is the main processing station. It uses ESA/ESOC software package NAPEOS [3] for GPS data cleaning (GNSSOBS) and Batch Least Square Estimator (BAHN). A sliding 24 hour arc is processed every time. The main characteristics of the estimation process are shown below:

• Polar motion and UT1 from GSN auxiliary data (EOP); • Undifferenced ionosphere free code and phase, 30s sampling; • Absolute phase centre offsets and variations of transmitter and receiver antennas (ANTEX format) [4]; • GSN predicted orbits and GPS clock bias decimated at 30s; • EIGEN-GL04C (120 x 120) gravity model; • IERS 2003 [5] Solid Earth tides; • FES 2004 ocean tides up to degree/order 20; • Sun, Moon and all Planets; • MSIS-90 model for atmospheric density; • Plate Model (fix surface) for drag, solar radiation and earth radiation; • Nominal yaw steering law1 • GPSP antenna reference point and centre of mass from CNES

Estim a ted Parameters: • Satellite state vector • 1 drag coefficients every 6 hours • 1 sets of CPR’s (along and cross track direction) every 6 hours

Finally after the estimation process has finished; a post processing and validation script windows the estima t ed orbit to the product length (usually the last orbit, two orbits in case of a blind orbit), extrac t ing some indicators of the estimation process and comparing it to any reference orbit if availa b le. The S4P Graphical User Interface is shown in Fig. 4.

1nominal yaw steering law is assumed as quaternions are currently not available in NRT.

Fig. 4. S4P Graphic User Interface for J2 NRT POD

4. RESULTS The reference ephemerides considered are the official POE orbits computed by CNES. In order to asses the level of accuracy achievable by the current software package available at EUMETSAT, and its currently implemented models; an offline POD using the best auxiliary GPS auxiliary data available (IGS final products [6]) is performed. A similar estimator configuration as the one described above is used, being the main difference (apart of course from the different GPS auxiliary data), the use of quaternions to describe the satellite attitude, instead of the nominal yaw steering law, used in the NRT system. Fig 5 shows the radial RMS achieved by this method for a period of almost two months (May 7th to June 30th 2009). The radial RMS for the complete period is 1.56cm. It has to be noted that a bias of 0.34cm exists, which is being investigated, and would improve the results.

Fig 5. Radial difference [cm] between EUM offline POD and CNES POE (reference)

In Fig. 6, the on-board computed orbit by the DIODE and embedded in the OGDR products, and the EUMETSAT GSN based NRT orbits are both compared against the reference POE orbit.

Fig. 6. Radial difference [cm] for OGDR (up) and EUM NRT POD(down) vs CNES POE (reference)

As expected, the accuracy obtained with the described processing strategy is slightly better than the official OGDR products with almost the same timeliness; radial RMS for the OGDR products is 4.2cm whereas EUMETSAT GSN based NRT POD presents a radial RMS of 3.7cm for the studied period. The timeliness of the EUMETSAT NRT POD product for a selected time period is shown in Fig. 7. Jason-2 OGDR specification of 3h latency for 75% of the products and 5h for 95% is nearly met. It should be noted that latencies around 4 hours are due to the blind orbits of the mission, and latencies over 6 hours are due to manual re-run of some failed processes.

Fig. 7. Latency distribution of EUM NRT POD product

5. POSSIBLE ACCURACY IMPROVEMENTS There are still some areas in the system that may be changed / improved in order to get better accuracies in the NRT POD.: • Using Quaternions instead of the nominal attitude law • Using improved auxiliary GPS data • Delaying the timeliness • Improving models in the POD software

5.1. Use of Quaternions instead of the nominal attitude law Jason- 2 guidance law presents a nadir pointing mode and a yaw steering mode. The nadir pointing is needed for the correct operation of the altimeter, while the purpose of the yaw steering mode is to point the solar arrays in a quasi-optimal way towards the sun during the satellite orbit, whatever the local time of the orbital plane is, of course turning around the nadir axis. While the nadir pointing is of high importance for the correct Jason-2 operation, the yaw angle of the satellite hasn’t such a strong constraint. The yaw angle has two main operation modes plus the transition phases between them. The first mode is active yaw steering for angles β between the orbital plane and the sun position vector larger than 15deg. or smaller than -15deg. For β angles between -15 and 15deg, the satellite is kept on fixed yaw mode. Comparing the nominal yaw steering mode against the real followed attitude given by the quaternions, show differences of up to 1.5deg in the satellite yaw angle for the yaw steering mode, but a negligible error for the fixed yaw mode. Fig. 8 shows the errors in the yaw angle (ψ) that arise by using the nominal attitude model instead of the quaternions. The epochs where the yaw mode change (10th, 15th and 20th June) show a larger error, as the transition is not modelled. The error in the yaw angle turns into an error of up to 4cm in the GPS antenna position.

Fig. 8. Error of the attitude model vs the real attitude given by the quaternions

The use of quaternions is technically possible as the information is contained in the satellite telemetry, but unfortunately at EUMETSAT the decoding software is not available. Fig. 9 shows the RMS of a simulated NRT POD for the yaw steering period but using quaternions instead of the nominal attitude model. This shows an increment of accuracy of almost 0.5cm radial RMS.

Fig. 9. Radial difference [cm] between simulated EUM NRT POD (quaternions) and CNES POE

5.2. Use of improved auxiliary GPS data Being the GSN GPS auxiliary data of high reliability, its accuracy can be further improved. The GSN system is currently operated with an ancient ESOC software package, and an imminent change to use the NAPEOS package is foreseen. This will result in better accuracy of the data, and therefore in better accuracy of the J2 POD. As an example, the ´Deutsches Zentrum für Luft- und Raumfahrt´ (DLR) is kindly providing on a best effort basis their RETICLE NRT clock corrections to the IGS ultra-rapid products [7], and recent runs performed at EUMETSAT show that Jason-2 POD performed with the DLR products achieves a higher accuracy than the ones based on the GSN. Fig. 10. presents a NRT POD run with RETICLE auxiliary data, showing an increment of accuracy of almost 1cm radial RMS; however it has to be noted that a) the time period is different as all the others shown in this paper, and b) the comparison is performed against MOE orbit, due to the unavailability of the POE orbits at the time of writing (5-6 weeks latency).

Fig. 10. Radial difference [cm] between simulated EUM NRT POD (DLR) and CNES MOE

5.3. Delaying of timeliness Due to the fact that a 24h LSQ batch is run for the NRT POD, where only the last part of the arc (the last orbit) is used as NRT product, it is possible to slide the batch window, by taking e.g the previous to the last orbit as an enhanced NRT product. On one hand the timeliness is delayed by one orbit, but on the other hand, moving the orbit to be estimated from the tail of the estimation arc, avoids the well known tail effects in LSQ estimators. Such an approach is followed by the best effort basis service provided by JPL / NOAA and called GPS-OGDR product. This product exhibits a significant higher radial accuracy of the orbit than the official OGDR products but delaying the timeliness of the product by one orbit. Fig. 11 shows the radial difference of such ‘delayed’ NRT POD produced at EUMETSAT against the reference POE orbits. The accuracy improvement in this case is approximately 1cm radial RMS.

Fig. 11. Radial difference [cm] between ‘delayed ‘ EUM NRT POD and CNES POE

5.4. Models in the POD software. Current version of NAPEOS software package used at EUMETSAT has some missing models (e.g. phase wind-up) and is missing other Jason specific models (i.e. wing-box model for drag and solar radiation, etc) that certainly improve the orbit accuracy. A major update of the NAPEOS package at EUMETSAT is planned in the near future, that provides these enhancements. Preliminary offline studies performed at ESOC show radial RMS differences with POE orbits of the order of 0.8cm, i.e. an increment of 0.7cm RMS compared to current EUMETSAT best results.

5.5. Performance Summary Table 1 summarizes the latency and accuracy of all presented orbits for the studied period. Mean and sigma is presented for Radial, Cross Track and Along Track and RMS for the 3D differences. All EUMETSAT solutions present a bias of approximate 3.5mm in the radial direction, which is being investigated.

Table 1.Summary of the latency and accuracy of the different precise orbit determination solutions Orbit Name Latency Radial CrossTrack Along Track 3D [cm] [cm] [cm] [cm] MOE 1.5 days -0.0 ± 1.6 +0.1 ± 6.7 -0.8 ± 0.4 8.0

OGDR 3-5 hours -0.1 ± 4.2 -0.2 ± 23.1 +6.3 ± 11.0 26.7

EUM_IGS 3-4 weeks +0.3 ± 1.5 +0.7 ± 2.2 -0.2 ± 3.7 4.6

EUM_GSN 3-5 hours +0.4 ± 3.7 +1.7 ± 4.9 -2.7 ± 8.9 11.3

EUM_GSN 3-5 hours +0.4 ± 3.3 +2.5 ± 5.0 -1.5 ± 8.2 10.6 Quaternions (simulated) EUM_GSN 5-7 hours +0.3 ± 2.8 +1.7 ± 4.2 -2.2 ± 7.0 9.0 Delay EUM_DLR 3-5 hours +0.4 ± 2.8 +0.6 ± 6.6 -1.6 ± 6.1 9.6

All orbits are co mpared against POE, except EUM_DLR, which is c ompared against MOE.

6. CONCLUS ION EUMETSAT has setup a NRT P OD system that takes benefit of the in-house available GPS auxiliary data provided b y the GRAS GSN System and uses the data from the GPSP receiver on-board Jason-2 in order to com pute Jason-2 prec ise orbits in NRT based on GPS data. EUMETSAT has demonstrated that the achiev able accuracy and latency of such an orbit is within the specification and already presents slightly better accuracy than the current NRT precise orbit present in the official Jason-2 OGDR product for the studied p eriod. EUMETSAT NRT POD is expected to improve its accuracy in the near future, due to some enh an cements to the POD system.

Such a POD system would provide a high accuracy NRT product useful both for redundancy and easy near real time validation of the official OGDR products.

7. ACKNOWLEDGMENTS The autho rs would lik e to thank André Hauschild from DLR for kindly providing access to DLR´s GPS real-time clock estimation product (RETICLE), and Oliver Montenbruck (DLR), Claudia Flohrer (ESA/ESOC) and Michiel Otten (ESA/ESOC) for their help and support with Jason-2 modelling and with the NAPEOS software package. 8. REFERENCES [1] R. Zandbergen and J. Dow. Sounding the atmosphere - ground support for GNSS radio-occultation processing. ESA Bulletin, 126:48–53,May 2006.

[2] Lynnes, C., Vollmer, B., Berrick, S., Mack, R., Pham, L., and Zhou, B, “Simple, Scalable, Script- Based Science Processor (S4P),” Geoscience and Remote Sensing Symposium, Vol. 1, IEEE, 2001, pp. 1465-1467.

[3] Águeda, A., and Zandbergen, R., “NAPEOS mathematical models and algorithms”, NAPEOS-MM- 01, Issue 3.0, ESA/ESOC, Darmstadt, 2004.

[4] R. Schmid, P. Steigenberger, G. Gendt, M. Ge, M. Rothacher, „Generation of a consistent absolute phase center correction model for GPS receiver and satellite antennas“, Journal of Geodesy, Vol. 81, No. 12, pp 781-798, 2007

[5] D.D. McCarthy, G. Petit, “IERS Technical Note No. 32 (2003)”, Verlag des Bundesamts für Kartographie und Geodäsie, Frankfurt am Main, Germany, 2004

[6] Dow, J. M., Neilan, R. E., and Gendt, G., “The International GPS Service (IGS): Celebrating the 10th Anniversary and Looking to the Next Decade,” Advanced Space Research, Vol. 36, No. 3, 2005, pp. 320-326.

[7] Hauschild A., Montenbruck O.;Real-time Clock Estimation for Precise Orbit Determination of LEO-Satellites; ION-GNSS-2008 Conference; 16-19 Sept. 2008; Savannah, Georgia (2008).

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