ETRI Journal

Electronics and Telecommunications Research Institute (한국전자통신연구원)
권호 표지
DOI QR코드

DOI QR Code

Optimized Station to Estimate Atmospheric Integrated Water Vapor Levels Using GNSS Signals and Meteorology Parameters

  • Beldjilali, Bilal (Tlemcen Telecommunications Laboratory, Faculty of Technology, Abou Bekr Belkaid University of Tlemcen) ;
  • Benadda, Belkacem (Tlemcen Telecommunications Laboratory, Faculty of Technology, Abou Bekr Belkaid University of Tlemcen)
  • Received : 2016.02.14
  • Accepted : 2016.08.08
  • Published : 2016.12.01
Download PDF
⟨ Previous Next ⟩

Abstract

The atmospheric meteorology parameters of the earth, such as temperature, pressure, and humidity, strongly influence the propagation of signals in Global Navigation Satellite Systems (GNSSs). The propagation delays associated with GNSS signals can be modeled and explained based on the atmospheric temperature, pressure, and humidity, as well as the locations of the satellites and receivers. In this paper, we propose an optimized and simplified low cost GNSS base weather station that can be used to provide a global estimate of the integrated water vapor value. Our algorithm can be used to measure the zenith tropospheric delay based on the measured propagation delays in the received signals. We also present the results of the data measurements performed at our station located in the Tlemcen region of Algeria.

Keywords

References

  1. X. Li, "Precise Positioning with Current Multi-constellation Global Navigation Satellite Systems: GPS, GLONASS, Galileo and BeiDou," Scientific Reports, vol. 5, 2015.
  2. X. Li, "Accuracy and Reliability of Multi-GNSS Real-Time Precise Positioning: GPS, GLONASS, BeiDou, and Galileo," J. Geodesy, vol. 89, no. 6, June 2015, pp. 607-635. https://doi.org/10.1007/s00190-015-0802-8
  3. I.G. Petrovski and T. Tsujii, Digital Satellite Navigation and Geophysics, New York, USA: Cambridge University Press, 2012.
  4. S. Jin, E. Cardellach, and F. Xie, GNSS Remote Sensing Theory, Methods and Applications, New York, USA: Springer, 2014.
  5. K. Teke et al., "Troposphere Delays from Space Geodetic Techniques, Water Vapor Radiometers, and Numerical Weather Models Over a Series of Continuous VLBI Campaigns," J. Geodesy, vol. 8, no. 10. Nov. 2013, pp. 981-1001.
  6. L. Wei et al., "A New Global Zenith Tropospheric Delay Model IGGtrop for GNSS Applications," Chinese Sci. Bulletin, vol. 57, no. 17, June 2012, pp. 2132-2139. https://doi.org/10.1007/s11434-012-5010-9
  7. S.W. Lee et al., "Monitoring Precipitable Water Vapor in Real-Time using Global navigation satellite systems," J. Geodesy, vol. 87, no. 10, Nov. 2013, pp. 923-934. https://doi.org/10.1007/s00190-013-0655-y
  8. X. Li et al., "Multi-GNSS Meteorology: Real-Time Retrieving of Atmospheric Water Vapor from BeiDou, Galileo, GLONASS and GPS Observations," IEEE Trans. Geosci. Remote Sens., vol. 53, no. 12, Dec. 2015, pp. 6385-6393. https://doi.org/10.1109/TGRS.2015.2438395
  9. X. Li et al., "Real-Time GPS Sensing of Atmospheric Water Vapor: Precise Point Positioning with Orbit, Clock and Phase Delay Corrections," Geophys. Res. Lett., vol. 41, no. 10, May 2014, pp. 3615-3621. https://doi.org/10.1002/2013GL058721
  10. X. Li et al., "Retrieving of Atmospheric Parameters from Multi-GNSS in Real Time: Validation with Water Vapor Radiometer and Numerical Weather Model," J. Geophysical Res. Atmoshers, vol. 120, no. 14, July 2015, pp. 7189-7204. https://doi.org/10.1002/2015JD023454
  11. T. Schuler and G. Hein, "GNSS Meteorology on Moving Platforms," Institute of Geodesy and Navigation, University of Munich, InsideGNSS, Apr. 2006.
  12. M. Boccolari et al., "GPS Zenith Total Delays and Precipitable Water in Comparison with Special Meteorological Observations in Verona (Italy) during MAP-SOP," Ann. Geophysics, vol. 45, no. 5, Oct. 2002.
  13. M.F.B. Norazmi et al., "The Concept of Operational Near Real-Time GNSS Meteorology System for Atmospheric Water Vapour Monitoring over Peninsular Malaysia," Arabian J. Sci. Eng., vol. 40, no. 1, Jan. 2015, pp. 235-244. https://doi.org/10.1007/s13369-014-1481-0
  14. F. Alshawaf et al., "Accurate Estimation of Atmospheric Water Vapor Using GNSS Observations and Surface Meteorological Data" IEEE Trans. Geosic. Remote Sens., vol. 53, no. 7, July 2015, pp. 3764-3771. https://doi.org/10.1109/TGRS.2014.2382713
  15. C. Ramis, R. Romero, and S. Alonso, "Relative humidity" Meteorology Group. Department of Physics. University of the Balearic Islands, 07122 Palma de Mallorca, Spain.
  16. J. Saastamoinen, "Atmospheric Correction for the Troposphere and Stratosphere in Radio Ranging Satellites," in The Use of Artificial Satellites for Geodesy, Washington, DC, USA: Wiley, pp. 247-251.
  17. Atmega Datasheet. http://www.atmel.com/images/doc2545.pdf
  18. LM335 Precision Temperature Sensor Datasheet. http://www.ti.com/lit/ds/symlink/lm335.pdf
  19. SparkFun Barometric Pressure Sensor Breakout - MPL115A1 Datasheet. https://www.sparkfun.com/datasheets/Sensors/Pressure/MPL115A1.pdf
  20. HS 1101 RELATIVE HUMIDITY SENSOR Datasheet. https://www.parallax.com/sites/default/files/downloads/27920-Humidity-Sensor-Datasheet.pdf
  21. NRF24L01 Datasheet. https://www.sparkfun.com/datasheets/Components/SMD/nRF24L01Pluss_Preliminary_Product_Specification_v1_0.pdf
  22. Sparkfun SiGe GN3S Sampler v3 Datasheet. http://ccar.colorado.edu/gnss/files/SE4110L_Datasheet_Rev3.pdf