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In radioastronomy the interferometric measurement between radiotelescopes located relatively close to each other helps removing ionospheric effects. Unfortunately, in case of networks such as LOw Frequency ARray (LOFAR), due to long baselines (currently up to 1500 km), interferometric methods fail to provide sufficiently accurate ionosphere delay corrections. Practically it means that systems such as LOFAR need external ionosphere information, coming from Global or Regional Ionospheric Maps (GIMs or RIMs, respectively). Thanks to the technology based on Global Navigation Satellite Systems (GNSS), the scientific community is provided with ionosphere sounding virtually worldwide. In this paper we compare several interpolation methods for RIMs computation based on scattered Vertical Total Electron Content measurements located on one thin ionospheric layer (Ionospheric Pierce Points—IPPs). The results of this work show that methods that take into account the topology of the data distribution (e.g., natural neighbour interpolation) perform better than those based on geometric computation only (e.g., distance-weighted methods).
Wydawca
Czasopismo
Rocznik
Tom
Strony
13--28
Opis fizyczny
Bibliogr. 29 poz.
Twórcy
autor
- Space Radio-Diagnostics Research Centre, University of Warmia and Mazury, Olsztyn, Poland
autor
- Space Radio-Diagnostics Research Centre, University of Warmia and Mazury, Olsztyn, Poland
autor
- Space Radio-Diagnostics Research Centre, University of Warmia and Mazury, Olsztyn, Poland
autor
- CRC for Spatial Information, Victoria, Australia
autor
- Department of Applied Mathematics IV, Ionospheric Determination and Navigation Based on Satellite and Terrestrial Systems Research Team, Barcelona, Spain
Bibliografia
- 1. Belikov VV, Ivanov VD, Kontorovich VK, Korytnik SA, Semenov AYu (1997) The non-Sibsonian interpolation: a new method of interpolation of the value of a function on an arbitrary set of points. Comput Math Math Phys 37(1):9–15r
- 2. Buresova D, Nava B, Galkin I, Angling M, Stankov SM, Coisson P (2009) Data ingestion and assimilation in ionospheric models. Ann Geophys 52(3/4):235–253
- 3. Choi B-K, Lee W-K, Cho S-K, Park J-U, Park P-H (2010) Global GPS ionospheric modelling using spherical harmonic expansion approach. J Astron Space Sci 27(4):359–366. doi:10.5140/JASS.2010.27.4.359
- 4. Dąbrowski BP, Krankowski A, Błaszkiewicz L, Rothkaehl H (2016) Prospects for solar and space weather research with polish part of the LOFAR telescope. Acta Geophys 64(3):825–840. doi:10.1515/acgeo-2016-0028
- 5. Dumitru PD, Plopeanu M, Badea D (2013) Comparative study regarding the methods of interpolation. In: 1st European conference geodesy and geomatics engineering GENG’13 “Recent Advances in Geodesy and Geomatics Engineering”, 8–10 October, 2013, Antalya, Turkey, pp 45–52
- 6. Fortune S (1995) Voronoi diagrams and Delaunay triangulations. In: Toth CD, O’Rourke J, Goodman JE (eds) Handbook of discrete and computational geometry. CRC Press Inc, Boca Raton, pp 377–388
- 7. Hajj GA, Wilson BD, Wang C, Pi X, Rosen IG (2004) Data assimilation of ground GPS total electron content into a physics‐based ionospheric model by use of the Kalman filter. Radio Sci 39:RS1S05. doi:10.1029/2002RS002859
- 8. Han D, Yun H, Kee C (2013) Modeling of ionospheric delay for SBAS using spherical harmonics functions. Trans Nav Int J Marine Nav Safety Sea Transport 7(2):205–209. doi:10.12716/1001.07.02.07
- 9. Harman C, Johns M (2008) Voronoi natural neighbors interpolation. In: Proceeding of class of 2008 senior conference on computational geometry, Swarthmore College, Swarthmore, USA, 49–53
- 10. Hernandez-Pajares M, Juan JM, Sanz J (1999) New approaches in global ionospheric determination using ground GPS data. J Atmos Sol -Terr Phys 61:1237–1247
- 11. Hernández-Pajares M, Juan JM, Sanz J (1997) Neural network modeling of the ionospheric electron content at global scale using GPS data. Radiol Sci 32(3):1081–1089
- 12. Hernández-Pajares M, Juan JM, Sanz J, Colombo OL (2000) Application of ionospheric tomography to real-time GPS carrier-phase ambiguities resolution at scales of 400–1000 km and with high geomagnetic activity. Geophys Res Lett 27(13):2009–2012
- 13. Hernández-Pajares M, Juan JM, Sanz J, Aragón-Àngel A, García-Rigo A, Salazar D, Escudero M (2011) The ionosphere: effects, GPS modeling and the benefits for space geodetic techniques. J Geodyn 85(12):887–907. doi:10.1007/s00190-011-0508-5
- 14. Jakowski N, Wilken V, Schlueter S, Stankov S, Heise S (2005) Ionospheric space weather effects monitored by simultaneous ground and space based GNSS signals. J Atmos Sol-Terr Phys 67(12):1074–1084
- 15. Komjathy A, Wilson B, Pi X, Akopian Y, Dumett D, Iijima B, Verkhoglya-dova O, Mannucci AJ (2010) JPL/USC GAIM: on the impact of using COSMIC and ground-based GPS measurements to estimate ionospheric parameters. J Geophys Res 115:A02307. doi:10.1029/2009JA014420
- 16. Krankowski A, Shagimuratov II, Baran LW, Yakimova G (2007) The structure of the mid- and high-latitude ionosphere during the November 2004 storm event obtained from GPS observations. Acta Geophys 55(4):490–508. doi:10.2478/s11600-007-0033-3
- 17. Mandrake L, Wilson B, Wang C, Hajj G, Mannucci A, Pi X (2005) A performance evaluation of the operational Jet Propulsion Laboratory/Univer-sity of Southern California Global Assimilation Ionospheric Model (JPL/USC GAIM). J Geophys Res 110:A12306. doi:10.1029/2005JA011170
- 18. Moore EH (1920) On the reciprocal of the general algebraic matrix. Bull Am Math Soc 26(9):394–395
- 19. Orus R, Hernandez-Pajares M, Juan JM, Sanz J (2005) Improvement of global ionospheric VTEC maps by using kriging interpolation technique. J Atmos Sol-Terr Phys 67:1598–1609
- 20. Pi X, Wang C, Hajj GA, Rosen G, Wilson BD, Bailey GJ (2003) Estimation of E × B drift using a global assimilative ionospheric model: an observation system simulation experiment. J Geophys Res 108(A2):1075. doi:10.1029/2001JA009235
- 21. Pi X, Had GA, Wilson BD, Mannucci AJ, Komjathy A, Mandrake L, Wang C (2004). 3‐Dimensional assimilative ionospheric modelling for regions of large TEC gradient. In: Proceedings of ION 2004 national technical meeting, Satellite Division of the Institute of Navigation, 26–28 January 2004, San Diego, USA
- 22. Pi X, Mannucci AJ, Iijima BA, Wilson BD, Komjathy A, Runge TF, Akopian V (2009) Assimilative modeling of ionospheric disturbances with FORMOSAT-3/COSMIC and ground-based GPS measurements. Terr Atmos Ocean Sci 20(1):273–285. doi:10.3319/TAO.2008.01.04.01(F3C)
- 23. Schaer S (1999) Mapping and predicting the earth’s ionosphere using the global positioning system. Ph.D. thesis, Astronomical Institute, University of Bern, Switzerland
- 24. Scherliess L, Schunk RW, Sojka JJ, Thompson DC, Zhu L (2006) Utah State University global assimilation of ionospheric measurements Gauss-Markov Kalman filter model of the ionosphere: model description and validation. J Geophys Res 111:A11315. doi:10.1029/2006JA011712
- 25. Schunk RW (2002) Global assimilation of ionospheric measurements (GAIM). In: Proceedings of international ionospheric effects symposium, 7–9 May 2002, Alexandria, USA
- 26. Sibson R (1981) A brief description of natural neighbor interpolation. In: Barnett V (ed), Interpreting multivariate data, Wiley, Chichester, pp 21–36
- 27. Strangeways HJ, Kutiev I, Cander LR, Kouris S, Gherm V, Marin D, De La Morena B, Pryse SE, Perrone L, M. Pietrella, S. Stankov, L. Tomasik, Tulunay E, Tulunay Y, Zernov N, Zolesi B (2009) Near-Earth space plasma modelling and forecasting. Ann Geophys 52(3/4):255–271. doi:10.4401/ag-4579
- 28. Sukumar N, Moran B, Semenov AYu, Belikov VV (2001) Natural neighbour Galerkin methods. Int J Numer Meth Eng 50:1–27
- 29. Wang C, Hajj G, Pi X, Rosen IG, Wilson B (2004) Development of the global assimilative ionospheric model. Radio Sci 39:RS1S06. doi:10.1029/2002RS002854
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-09752158-3931-477f-b9e8-997106317468