The Australian Space Research Program Project Platform Technologies for Space Atmosphere and Climate

Transcription

1 International Global Navigation Satellite Systems Society IGNSS Symposium 2011 Sydney, Australia Nov, 2011 The Australian Space Research Program Project Platform Technologies for Space Atmosphere and Climate Kefei Zhang (1), Suqin Wu (1), Jizhang Sang (2), Brett Carter (1), Chuan-Sheng Wang (1), Robert Norman (1) (1) SPACE Research Centre, School of Mathematical and Geospatial Sciences, RMIT University, GPO Box 2476, Melbourne 3001, Australia. Tel: Fax: , (2) EOS Space Systems Pty Ltd, Mt Stromlo Observatory, Cotter Road, Weston Creek, ACT 2611, Australia. Tel: , Fax: ABSTRACT In this paper, the multi-million-dollar Australian Space Research Program Project Platform Technologies for Space Atmosphere and Climate recently awarded to a consortium led by RMIT University is introduced. This project is part of the Australian Government's recent space-related initiatives to support national strategic, economic and social objectives. The research consortium consists of RMIT University, the Australian Bureau of Meteorology, Curtin University of Technology, the University of New South Wales, Electro Optic Systems Space System, GPSat Systems Australia and National Central University of Taiwan in conjunction with National Space Organisation Taiwan and NOAA s World Data Centre for Meteorology. The main research of the project is focused on developing new algorithms, new approaches, and process optimisation to enhance Australia s capability in space-related research and to promote innovative applications of spacerelated cutting-edge technologies in Australia. The aims and objectives, primary research tasks and work packages of this project and anticipated outcomes will be outlined. Key issues related to the research work and challenges confronting Australian space research and space industry will be discussed, particularly those research tasks in the context of next generation GNSS and its innovative applications in the areas of space weather, space tracking, climate and positioning, navigation and timing (PNT) will be emphasised. Progresses made to date, selected major findings and preliminary results in the areas of PNT, space geodesy-based atmosphere sounding, climate change, space weather and environment will be presented. Finally, our view on the future of space research related to GNSS and space geodesy, which is a key component of the ever-expanding future Earth observation systems, will be given. KEYWORDS: space tracking, atmospheric modelling, GPS RO, ray-tracing 1

2 1. INTRODUCTION Geodesy is the science of measuring and monitoring the size and shape of the Earth including its gravity field and determining the location of points on and near the Earth s surface. The Global Navigation Satellite Systems (GNSS), such as GPS and Glonass, have become a critical space-based infrastructure and dominant technology for positioning and navigation to measure points on the ground, in the air and space. The following geodesy and GNSS related areas of research hence form an indispensable part of space research. the precise determination of space objects orbit, especially the determination and prediction of space objects in real-time or near real-time; precise positioning based on spatial observation techniques such as using Global Navigation Satellite System (GNSS) and Satellite Laser Ranging (SLR) techniques; the precise modelling of the atmosphere for the improvement of the accuracy of the determination and prediction of space objects; and using the atmospheric satellite remote sensing technique, e.g., the Radio Occultation (RO) technique, to derive atmospheric parameters including the temperature, pressure and water vapour in the stratosphere and the troposphere. The research and development of these topics are important for space situational awareness, the tracking and navigation of space objects, the surveillance of space debris, warning and avoidance of space objects collision for both existing satellites and the satellites to be launched, the maintenance and operation of the satellites in service, the monitoring of space weather and climate change etc. In order to keep up with the pace of advanced international research and to play a leading role internationally in the space-related research arena, RMIT University, in collaboration with its partners, took an initiative in late 2009 and an international team was formed to embark on this research (Zhang et al., 2009). This sizable research collaboration entitled Platform Technologies for Space, Atmosphere and Climate was supported by the Australian Space Research Program (ASRP) through a competitive process. The international consortium is a typical combination of industry academic/research and government from both Australia and other countries who are advanced in the related research areas. These consortium members are: RMIT University, the University of New South Wales (UNSW), Curtin University of Technology (CUT), Bureau of Meteorology (BoM), Electro Optic Systems Space System (EOSSS), GPSat Systems Australia (GSA), NOAA s World Data Center for Meteorology (WDCM), USA and National Space Organisation (Center of Space and Remote Sensing Research, National Central University (NCU)), Taiwan. 2. AIMS AND OBJECTIVES The aim of this project is to enhance Australia's space capabilities by developing integrated advanced space-based platform technologies through a multi-sensor satellite remote sensing approach. Fundamental, technical and application issues (benefits and new challenges) related to new generation navigation and geo-environmental remote sensing satellite systems will be investigated. The key objectives are as follows: to develop advanced algorithms for precise real-time in-space tracking and navigation, and precise orbit determination (POD) for the current and future geoenvironmental satellites; 2

3 to investigate atmospheric mass density models in order to improve the accuracy, reliability and efficiency of the determination of space objects and surveillance systems; to develop models and algorithms to explore the North American Aerospace Defence (NORAD) Two Line Element (TLE) catalogue of 10,000 space objects for a better prediction of space objects orbit; to develop new algorithms and optimisation procedures for high precision ubiquitous positioning and mapping in the context of new generation GNSS; to investigate the effects of the Earth s magnetic field, the troposphere, the stratosphere and the ionosphere on the electro-magnetic L-band frequency ray path, including the development of comprehensive 3-D ray tracing application software packages; to study the atmosphere, the ionosphere and space weather using GNSS and the low Earth orbit (LEO) radio occultation (RO) technique; to evaluate and assimilate multi-sensor satellite remote sensing data, and to develop space-based platform technologies for investigating climate change and climatic hazards; and to improve the characterisation of climate in the Australian region based on the new models, algorithms, methodologies developed and implemented in the applications software for this project. Apart from the above objectives, this research will also investigate new models and new algorithms to incorporate multi-constellation and multi-frequency GNSS observations that the new generation GNSS will provide. In addition, the new geo-environmental satellite programs (e.g. COSMIC II) can be made best use for addressing the problems that Australia faces with climate change and natural hazards such as tropical cyclones, drought, extreme heat and bushfires etc., and also for addressing the issue of the insufficient density of ground-based meteorological observation stations in the southern hemisphere and the lack of meteorological observation data over the world s oceans and polar regions. Thus in this project, it is proposed to explore the acquisition, processing and the analysis of more observation data, especially multi-sensor satellite remote sensing data, which the new geo-environmental satellite programs will offer for space, atmosphere and climate research, particularly in the Australian context. 3. RESEARCH ROADMAP This project covers four main research themes which are categorised into eight working packages (WPs). In these WPs, a suite of software and system platforms will be developed. This work includes the development of new algorithms, new models and comprehensive software packages to facilitate the optimal data acquisition, data processing and analysis, and applications of space tracking, the best use of the new generation GNSS and RO data as well as other meteorology-/climate-related measurements. The relationship among these four research areas, the associated eight WPs, the specific research topics and the organisations undertaking the research topics in each WP are shown in Figure 1. 3

4 Figure 1. Flowchart of the four key research themes and their associated eight work packages, and the road map displaying their relationships (Zhang et al., 2009). 4. RESEARCH RESULTS TO DATE Research in several aforementioned areas has been conducted by the research consortium. A large range of new developments across all the eight work packages has been achieved. This paper provides an outline over four selected recent results achieved (primarily by the RMIT team). They are briefly summarised as follows. 4.1 New Approach for Derivation of Atmospheric Mass Density Model For POD and the prediction of space objects orbits, one of the main limiting factors that affect the accuracy of POD and orbit prediction is the inaccuracy of atmospheric mass density models that are required in the dynamic orbit determination method. Developing high accuracy atmospheric mass density models is a very challenging task. One of the critical requirements for such developments is the availability of high quality (direct and indirect) observations of mass densities with sufficient spatial and temporal resolutions. For example, both CHAMP and GRACE missions have generated an unprecedented volume of high-quality measurements of the mass densities from the accelerometers onboard the satellites. However, the spatial and temporal coverage of these two missions is still limited by the accuracy of density models. Advances in satellite tracking and orbit determinations make the POD a routine practice for many LEO satellites. In particular, orbits of GPS-equipped satellites can be determined at an 4

5 accuracy of a few centimetres (Kang, et al., 2006; Jaggi, et al., 2007). Precision orbital data could be used to estimate atmospheric mass density. Picone et al. (2005) developed a method of estimating mass density from orbit data. However, the method estimates only one density parameter for an orbit fit span, which could be a few days. Bowman et al. (2004) developed a method of computing daily densities from satellite orbit data. A new method of estimating atmospheric mass densities with a high temporal resolution from precision orbit information has been developed. This method used the drag perturbation equation of the semi-major axis of a satellite orbit; the details on this approach can be found from Sang et al., (2011a, b). It was tested and validated using both simulation data and the IGS rapid orbit products (ROP) of the CHAMP satellite over a period of three months. The density results were compared with accelerometer-derived densities and then used to refine or calibrate the coefficients of the DTM78 model. An immediate application of the densities derived from the precise orbit data of some objects was the calibration of an existing density model. This calibrated model was then used for the orbit determinations of other non-calibrated objects, or for the orbit predictions of both the calibrated and non-calibrated objects. Figure 2 shows that using the calibrated model derived from the new approach and 24 hours of observation data to predict 10 days orbit of the CHAMP satellite, the prediction accuracy was significantly improved in comparison to the original density model results. In addition, when the coefficients of the DTM78 model were calibrated, the along-track orbit prediction error over a period of 24 hours was reduced from m to m (NB: this is not shown in Figure 2). Along Track Bias (m) Reduction of Orbit Prediction Errors Original Modified Time since start epoch (hours) Figure 2: Comparison of orbit prediction errors derived from the original and the calibrated models (Sang et al., 2011b). 4.2 Using GNSS RO technique to derive and analyse atmospheric parameters in the Australian region GNSS radio occultation (RO) is a remote sensing sounding technique in which L-band radio signals emitted from GNSS satellites pass through the Earth s atmosphere before arriving at the receiver onboard a LEO satellite. The atmosphere causes both propagation delay and bending of the GNSS signals along the ray paths between the GPS and LEO satellites. Based on the Abel transformation, a profile of bending angles derived from a RO event can be inverted into a profile of atmospheric refractivity index, and the dry temperature and pressure profiles can be obtained using the ideal gas law and assuming hydrostatic equilibrium. 5

6 In this study, the difference between the RO results derived from the Radio Occultation Processing Package (ROPP) and from the COSMIC Data Analysis and Archive Center (CDAAC) was investigated. The first step in ROPP data processing was the pre-processing of raw data; more specifically, the obtaining of the spatial spectra of the amplitude and the excess phase data. The radio holographic filter (Gorbunov and Lauritsen, 2006) and the quality control indicator (GRAS, 2010) were used for the correction of the highly noisy L2 data. In the phase of data processing, the geometric optics (GO) and wave optics (CT2) methods (Gorbunov and Lauritsen, 2004) were used for the computation of L1 and L2 bending angles as well as impact parameters for two altitude ranges. The GO and CT2 methods were used for the altitude ranges of above 25 km and below 25 km respectively. The FORMOSAT-3/COSMIC data in the period of January 1 to 3, 2010 in the Australian region ( E and S) were selected. The difference among the RO results from ROPP and the two versions of CDAAC, i.e., V and V , were analysed. The minimum difference of average refractivity at the altitudes of 5 35 km was (Event 1: C G19, E S ), and the maximum value in the same altitude range was (Event 2: C G02, E S ). These two events were used as examples for demonstrating the results of the comparisons made in this section, as shown in Figure 3. There was an offset between the bending angles from ROPP and CDAAC. The largest difference in the dry temperature results from the two software packages for Event 1 was 2.51 at km altitudes and 5.53 at 5 10 km altitudes for Event 2. The test results for the period of January 1 to 3, 2010 are as follows: 1) The profiles of dry temperature retrieved from ROPP and CDAAC had a good consistency at the altitudes of km. The differences between the results at all pressure levels in the profiles were less than 3 hpa for all the RO events. 2) The average difference between the pressure profiles at altitudes of 5 35 km from ROPP and CDAAC (V ) was in the range of hpa and the average difference of dry temperature was in the range of ) The average difference between the dry temperatures from ROPP and the two CDAAC versions approached 1.6 and 0.9 degrees at the altitude ranges of km and 5 10 km, respectively. 4) In the altitude range of km, the average difference of the dry temperatures from the two versions of CDAAC was about 0.06 degrees. However, there was no significant difference in the refractivity and pressure results derived from the two versions of CDAAC. It is concluded that the refractivity and pressure over the Australian region calculated from the different RO techniques have no significant difference. However, the difference between the dry temperatures derived from different RO techniques can be large, especially at the km altitudes. 6

7 3(a), Event 1 3(b), Event 2 Figure 3. The retrieved atmospheric profiles using ROPP and CDAAC (V and V ) for Event 1 (a) and Event 2 (b). 7

8 4.3 Developing numerical ray-tracing algorithms and software to determine satellite-tosatellite L-band radio frequency paths Numerical ray-tracing algorithms and software packages for the determination of satellite-tosatellite L-band radio frequency paths have been developed. A new 3-D numerical ray tube technique has been developed (Norman et al. 2011). The ray tracing technique can be applied to electromagnetic propagation in anisotropic media such as the Earth s ionosphere. The numerical ray tube technique requires eighteen differential equations representing the position and direction of the principle ray path as well as the two linearly independent variational ray paths. These eighteen differential equations are integrated simultaneously at each point along the principle ray. This ray tracing technique can be used to determine ray parameters such as the group path, phase path, angle of arrival, signal strength and it has a homing-in capability. The ray tracing program can trace the GPS signals from the GPS satellite to the LEO satellite using any ionospheric or atmospheric models to investigate the effect of these error sources on the signals. At present the IRI2007 model (Bilitza and Reinisch, 2008) is used for the ionospheric effect on the ray parameters. In addition, the birefringence effects due to the Earth s magnetic field on the ionosphere and the electromagnetic signal are also taken into account in our ray tracing program. Thus the extraordinary and ordinary ray paths can also be traced. 4.4 Space weather effects on RO GPS scintillation The COSMIC RO data are being used to investigate the average occurrences of high ionospheric scintillation events experienced on GNSS systems. In particular, the COSMIC RO database is being used to identify the physical factors that result in high ionospheric scintillation events across the globe. Included for each RO event in the COSMIC database is a time series of a proxy for the amplitude scintillation S4 index. The maximum S4 value measured during each event, in addition to its corresponding location, local time (LT) and the 9-second average encompassing the time that the maximum S4 was measured, are used to study the statistical ionospheric scintillation trends. Fig 4 shows the magnetic latitude (MLAT) LT distributions of the high-scintillation (i.e. 'S4max9s' 0.6) event occurrence in the lower-f region (altitudes km), measured in four separate longitude sectors (rows) for low and moderate geomagnetic activity (columns) as specified by the Kp index. From Fig 4, it is clear that the high-scintillation events are common at locations close to the magnetic equator for periods of low geomagnetic activity. However, the exact occurrence probabilities vary significantly between the longitude sectors and for moderate geomagnetic activity levels. The high-scintillation events are far more common in the American sector as compared to the other sectors. Further, the range of LTs and MLATs that indicate high occurrence of highscintillation levels change with increasing geomagnetic activity; e.g. in the American sector the range of MLATs (LTs) where high-scintillations are above ~ 30 % is 35 S 25 N (19 24 LT) for low activity and 40 S 25 N (19 01 LT) for moderate activity. In an accompanying paper by Carter et al (2011), it is further demonstrated that the COSMIC RO dataset is also sufficient to study the seasonal variations in the average scintillation values for each of these longitude sectors. This work on GPS RO scintillation has the potential to significantly augment our current understanding of the effects of ionospheric plasma bubbles on GNSS applications by 8

9 providing an unrivalled spatial and temporal coverage of the high-scintillation band across the magnetic equator. As a result, a better understanding of the environmental factors that drive the production of ionospheric plasma bubbles will be obtained and our ability to forecast them will be significantly improved. Figure 4. Magnetic latitude (MLAT) local time (LT) plots that display the percentage occurrence of high-scintillation ('S4max9s' 0.6) RO events during in the lower-f region (altitudes km). The columns represent the data collected during periods of low and moderate geomagnetic activity, respectively. Each row displays the data from RO events that occurred within the 90 -wide longitude sector as labelled in the top-left. For reference, the American sector spans 110 E to 20 E in geographic longitude, followed by the African ( 20 E to 70 E), Asian (70 E to 160 E) and Pacific (160 E to 110 E) sectors. 5. SUMMARY AND CONCLUDING REMARKS A detailed description of the recently awarded ASRP project including the main aims and objectives, research themes and WPs, and expected outcomes are presented. The primary research areas covered include space, atmosphere and climate. Researchers from several prestigious universities, organisations and industry sections over the world have already collaborated to undertake a variety of research tasks proposed in this project. This research will have a significant impact on efficient and effective space tracking, precise satellite positioning, atmosphere and climate monitoring etc., in the Australian context. The platforms to be developed will enhance our capacity and play a critical role in supporting the Australian space industry for technological innovation and future Australian satellite missions. It will develop critical space-based technology platforms and improve our understanding of the Australian climate and thus contribute to the wellbeing of our community. Four selected topics of research results from the SPACE research team, at RMIT University, are presented. The promising results will pave the way for further progress in the related research areas for this project. 9

10 ACKNOWLEDGEMENTS: The authors would like to gratefully acknowledge the Australian government s research grant support for this project through the Australian Space Research Program (ASRP) project of The Department of Innovation, Industry, Science and Research (DIISR). REFERENCES Bilitza D, Reinisch B (2008) International Reference Ionosphere 2007: Improvements and new parameters, Journal of Advances in Space Research, 42(4): Bowman BR, Marcos FA, Kendra MJ (2004) A Method for Computing Accurate Daily Atmospheric Density Values from Satellite Drag Data, AAS , 14th AAS/AIAA Space Flight Mechanics Conference, Maui, Hawaii, February 8 12, Carter BA, Norman R, Wang C, Li Y, Gordon S, Hooper G, Zhang K (2011) Space weather effects on the GPS scintillation levels received from radio occultations, IGNSS Symposium, November, 2011, Sydney, New South Wales. Gorbunov ME, Lauritsen KB (2004) Analysis of wave fields by Fourier integral operators and their application for radio occultations, Radio Science, 39(RS4010), doi: /2003rs Gorbunov ME, Lauritsen KB (2006) Radio holographic filtering of noisy radio occultations, Atmosphere and Climate Studies by Occultation Methods, edited by U. Foelsche, G. Kirchengast, and A. Steiner, Springer, Berlin, Heidelberg. GRAS Meteorology (2010) The Radio Occultation Processing Package (ROPP) User Guide Part III: Pre-processor module, V4.1, EUMETSAT Satellite Application Facility. Jaggi A, Hugentobler U, Bock H, Beutler G (2007) Precise Orbit Determination for GRACE Using Undifferenced or Doubly Differenced GPS Data, Advances in Space Research, 39: Kang Z, Tapley B, Bettadpur S, Ries J, Nagel P, Pastor, R. (2006) Precise Orbit Determination for the GRACE Mission Using only GPS Data, Journal of Geodesy, 80: Norman RJ, Bennett JA, Dyson PL, Le Marshall J, Zhang K (2011) A ray-tracing technique for determining ray tubes in anisotropic media, submitted to IEEE Transactions on Antennas and Propagation. Picone JM, Emmert JM, Lean JL (2005) Thermospheric Densities Derived from Spacecraft Orbits: Accurate Processing of Two-line Element Sets, Journal of Geophysical Research, 110: A Sang J, Smith C, Zhang K (2011a) Modification of Atmospheric Mass Density Model Coefficients Using Space Tracking Data A Simulation Study for Accurate Debris Orbit Prediction, AAS , 21 st Space Flight Mechanics Meeting, February 2011, New Orleans, Louisiana. Sang J, Smith C, Zhang K (2011b) Towards Accurate Atmospheric Mass Density (Determination) using Precise Positional Information of Space Objects, submitted to Advances in Space Research. Zhang K, Teunisen P, Rizos C, Le Marshall J, Kuleshov Y, Sang J, Hooper G, Liou Y, Diamond H, Lim S and Odijk (2009) Platform Technologies for Space, Atmosphere and Climate, Research Proposal submitted to The Australia Space Research Program Stream B Space Innovation and Research Project, The Space Policy Unit of DIISR, 81p. 10