Journal of Geodesy

, Volume 89, Issue 6, pp 519–536 | Cite as

GPS radio occultation constellation design with the optimal performance in Asia Pacific region

  • Milad Asgarimehr
  • Masoud Mashhadi Hossainali
Original Article


The growing desire for better spatial and also temporal distribution of radio occultation data is a motivation for extensive researches considering either number of GNSS/receiver satellites or better optimization tools resulting in better distributions. This paper addresses the problem of designing a global positioning system-only radio occultation mission with the optimal performance in Asia Pacific region. Constellation Patterns are discussed and 2D-lattice and 3D-lattice flower constellations are adopted to develop a system with circular and elliptical orbits, respectively. A perturbed orbit propagation model leading to significantly more accurate pre-analysis is used. Emphasizing on the spatial and also temporal distribution of radio occultation events for the first time, distribution norm is provided as a volumetric distribution measure using Voronoi diagram concept in a 3D space consisting temporal and spatial intervals. Optimizations are performed using genetic algorithm to determine optimal constellation design parameters by the suitable fitness function and constraints devised. The resulted constellation has been evaluated by a regional comparison to the globally distributed FORMOSAT-3/COSMIC in terms of the distribution norm, number of radio occultation events and also coverage as an additional point-to-point distribution measure. Although it is demonstrated that the optimal 3D-lattice enjoys better performance than FORMOSAT-3, the design approach results in a 2D-lattice flower constellation which is superior to other constellations in regional emphasis of radio occultation events. Its global performance is discussed and it is demonstrated that using multi-GNSS receiver to increase satellites may not guarantee a good distribution of radio occultation data in some aspects.


Constellation design Radio occultation mission Genetic algorithms Constellation patterns Voronoi diagram  FORMOSAT-3/COSMIC 


  1. Abdelkhalik O, Gad A (2011) Optimization of space orbits design for Earth orbiting missions. Acta Astronautica 68:1307–1317. doi: 10.1016/j.actaastro.2010.09.029
  2. Anthes R (2011) Exploring Earth’s atmosphere with radio occultation: contributions to weather, climate and space weather. Atmos Meas Tech 4:1077–1103CrossRefGoogle Scholar
  3. Asvial M, Tafazolli R, Evans BG (2004) Satellite constellation design and radio resource management using genetic algorithm. Communications, IEEE proceedings, pp 151:204–209. doi: 10.1049/ip-com:20040291(410)151
  4. Aurenhammer F (1991) Voronoi diagrams—a survey of a fundamental geometric data structure. ACM Comput Sur (CSUR) 23:345–405CrossRefGoogle Scholar
  5. Avendaño ME, Davis JJ, Mortari D (2013) The 2-D lattice theory of fower constellations. Celest. Mech. Dyn. Astron. 116:325–337CrossRefGoogle Scholar
  6. Bevis M, Businger S, Chiswell S, Herring TA, Anthes RA, Rocken C, Ware RH (1994) GPS meteorology: mapping zenith wet delays onto precipitable water. J Appl Meteorol 33:379–386CrossRefGoogle Scholar
  7. Brunini C, Azpilicueta F, Nava B (2013) A technique for routinely updating the ITU-R database using radio occultation electron density profiles. J Geod 87:813–823CrossRefGoogle Scholar
  8. Coesa U (1976) Standard atmosphere, 1976. US Government Printing Office, Washington, DCGoogle Scholar
  9. Cook G (1965) Satellite drag coefficients. Planet Space Sci 13:929–946CrossRefGoogle Scholar
  10. Cook K, Fong C-J, Wenkel MJ, Wilczynski P, Yen N, Chang G (2013) FORMOSAT-7/COSMIC-2 GNSS radio occultation constellation mission for global weather monitoring. In: Aerospace conference, 2013 IEEE. IEEE, pp. 1–8Google Scholar
  11. Crossley WA, Williams EA (2000) Simulated annealing and genetic algorithm approaches for discontinuous coverage satellite constellation design. Eng Optim 32:353–371. doi: 10.1080/03052150008941304 CrossRefGoogle Scholar
  12. Davis JJ, Avendaño ME, Mortari D (2013) The 3-D lattice theory of flower constellations. Celest Mech Dyn Astron 116:339–356CrossRefGoogle Scholar
  13. Douglas M (2010) Adaptive sounding arrays for tropical regions. In: Extended abstracts, 29th conference on Hurricanes and Tropical Meteorology. Am Meteor Soc Tucson, AZ, pp 12B. 17Google Scholar
  14. Ely T, Crossley W, Williams E (1999) Satellite constellation design for zonal coverage using genetic algorithms. J Astronaut Sci 47:207–228Google Scholar
  15. Flores F, Rondanelli R, Díaz M, Querel R, Mundnich K, Herrera LA, Pola D, Carricajo T (2013) The life cycle of a radiosonde. Bull Am Meteorol Soc 94:187–198CrossRefGoogle Scholar
  16. Fong C-J, Shiau W-T, Lin C-T, Kuo T-C, Chu C-H, Yang S-K, Yen NL, Chen S-S, Kuo Y-H, Liou Y-A (2008) Constellation deployment for the FORMOSAT-3/COSMIC mission. IEEE Trans Geosci Remote Sens 46:3367–3379CrossRefGoogle Scholar
  17. Fong C-J, Yen NL, Chu C-H, Yang S-K, Shiau W-T, Huang C-Y, Chi S, Chen S-S, Liou Y-A, Kuo Y-H (2009) FORMOSAT-3/COSMIC spacecraft constellation system, mission results, and prospect for follow-on mission. Terrestrial, Atmospheric and Oceanic Sciences 20Google Scholar
  18. Fonseca CM, Fleming PJ (1993) Genetic algorithms for multiobjective optimization: formulation discussion and generalization. In: ICGA, pp 416–423Google Scholar
  19. Goldberg D, Holland J (1988) Genetic algorithms and machine learning. Mach Learn 3:95–99. doi: 10.1023/A:1022602019183 CrossRefGoogle Scholar
  20. Gunzburger M, Burkardt J (2004) Uniformity measures for point sample in hypercubes. Rapp. tech. Florida State University (cf. p 73)Google Scholar
  21. Hogan P, Gaskins T (2009) Spatial information processing: standards-based open source visualization technology. In: AGU fall meeting abstracts, p 04Google Scholar
  22. James RW, Wiley JL (1999) Space mission analysis and design. MicrocosmPress, TorranceGoogle Scholar
  23. Juang J-C, Tsai Y-F, Chu C-H (2013) On constellation design of multi-GNSS radio occultation mission. Acta Astronaut 82:88–94CrossRefGoogle Scholar
  24. Kessler DJ (1990) Collision probability at low altitudes resulting from elliptical orbits. Adv Space Res 10:393–396CrossRefGoogle Scholar
  25. Kliore A, Cain DL, Levy GS, Eshleman VR, Fjeldbo G, Drake FD (1965) Occultation experiment: results of the first direct measurement of Mars’s atmosphere and ionosphere. Science 149:1243–1248CrossRefGoogle Scholar
  26. Le Marshall J, Xiao Y, Norman R, Zhang K, Rea A, Cucurull L, Seecamp R, Steinle P, Puri K, Fu E (2012) The application of radio occultation observations for climate monitoring and numerical weather prediction in the Australian region. Aust Meteorol Oceanogr J 62:323–334Google Scholar
  27. Lee S, Mortari D (2013) 2-D Lattice flower constellations for radio occultation missions. Front Aerosp Eng 2:79–90Google Scholar
  28. Mortari D, Wilkins MP (2008) Flower constellation set theory. Part I: compatibility and phasing. IEEE Trans Aerosp Electron Syst 44:953–962CrossRefGoogle Scholar
  29. Mortari D, Wilkins MP, Bruccolerr C (2003) The flower constellations. Adv Astronaut Sci 115:269–290Google Scholar
  30. Mousa A, Aoyama Y, Tsuda T (2006) A simulation analysis to optimize orbits for a tropical GPS radio occultation mission. Earth Planets Space 58:919–925CrossRefGoogle Scholar
  31. Poli R, Langdon WB (1998) Schema theory for genetic programming with one-point crossover and point mutation. Evolut Comput 6:231–252CrossRefGoogle Scholar
  32. Rider L (1985) Optimized polar orbit constellations for redundant earth coverage. J Astronaut Sci 33:147–161Google Scholar
  33. Rider L (1986) Analytic design of satellite constellations for zonal earth coverage using inclined circular orbits. J Astronaut Sci 34:31–64Google Scholar
  34. Seeber G (2003) Satellite geodesy: foundations, methods, and applications. Walter de Gruyter, BerlinCrossRefGoogle Scholar
  35. Speckman L, Lang T, Boyce W (1990) An analysis of the line of sight vector between two satellites in common altitude circular orbits. In: Astrodynamics conference. American Institute of Aeronautics and AstronauticsGoogle Scholar
  36. Walker J (1978) Satellite patterns for continuous multiple whole-Earth coverage. In: Maritime and aeronautical satellite communication and navigation, pp 119–122Google Scholar
  37. Walker JG (1977) Continuous whole-earth coverage by circular-orbit satellite patterns. In: DTIC Document, United KingdomGoogle Scholar
  38. Wickert J, Michalak G, Schmidt T, Beyerle G, Cheng C-Z, Healy SB, Heise S, Huang C-Y, Jakowski N, Kohler W (2009) GPS radio occultation: results from CHAMP, GRACE and FORMOSAT-3/COSMIC. Terr Atmos Ocean Sci 20:35Google Scholar
  39. Wilkins MP, Mortari D (2008) Flower constellation set theory part II: secondary paths and equivalency. IEEE Trans Aerosp Electron Syst 44:964–976CrossRefGoogle Scholar
  40. Wu B-H, Chu V, Chen P, Ting T (2005) FORMOSAT-3/COSMIC science mission update. GPS Solut 9:111–121CrossRefGoogle Scholar
  41. Xu G (2008) Orbits. Springer, HeidelbergGoogle Scholar
  42. Yan K, Yang F, Pan C, Song J, Ren F, Li J (2013) Genetic algorithm aided gray-APSK constellation optimization. In: Wireless communications and mobile computing conference (IWCMC), 2013 9th international. IEEE, pp 1705–1709Google Scholar
  43. Yunck TP, Chao-Han L, Ware R (2000) A history of GPS sounding. Terr Atmosp Ocean Sci 11:1–20Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Department of Geodesy and Geomatics EngineeringK. N.Toosi University of TechnologyTehranIran

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