Abstract
A method is presented for real-time validation of GNSS measurements of a single receiver, where data from each satellite are independently processed. A geometry-free observation model is used with a reparameterized form of the unknowns to overcome rank deficiency of the model. The ionosphere error and non-constant biases such as multipath are assumed changing relatively smoothly as a function of time. Data validation and detection of errors are based on statistical testing of the observation residuals using the detection–identification–adaptation approach. The method is applicable to any GNSS with any number of frequencies. The performance of validation method was evaluated using multi-frequency data from three GNSS (GPS, GLONASS, and Galileo) that span 3 days in a test site at Curtin University, Australia. Performance of the method in detection and identification of outliers in code observations, and detection of cycle slips in phase data were examined. Results show that the success rate vary according to precision of observations and their number as well as size of the errors. The method capability is demonstrated when processing four IOV Galileo satellites in a single-point-positioning mode and in another test by comparing its performance with Bernese software in detection of cycle slips in precise point-positioning processing using GPS data.
Similar content being viewed by others
References
Baarda WA (1968) Testing procedure for use in geodetic networks. Netherlands Geodetic Commission, Publications on Geodesy, New Series 2(5)
Banville S, Langley R (2010) Instantaneous cycle-slip correction for PPP. Navigation 57(4):325–334
Blanch J, Walter T, Enge P (2010) RAIM with optimal integrity and continuity allocations under multiple failures. IEEE Trans Aerosp Electron Syst 46(3):1235–1247
Blewitt G (1990) An automatic editing algorithm for GPS data. Geophys Res Lett 17(3):199–202
Dach R, Hugentobler U, Fridez P, Meindl M (2007) Bernese GPS Software Version 5.0. Publications of Astronomical Institute, University of Bern
De Bakker PF, Van der Marel H, Teunissen PJG (2009a) The minimal detectable bias for GNSS observations with a single receiver setup and a geometry-free model. In: Proceedings of the ENC-GNSS 2009, Naples, Italy, 3–6 May 2009
De Bakker PF, Van der Marel H, Tiberius CCJM (2009b) Geometry-free undifferenced, single and double differenced analysis of single frequency GPS, EGNOS and GIOVE-A/B measurements. GPS Solut 13:305–314
De Jong K, Teunissen PJG (2000) Minimal detectable biases of GPS observations for a weighted ionosphere. Earth Planets Space 52:857–862
De Jong K, Van der Marel H, Jonkman N (2001) Real-time GPS and Glonass integrity monitoring and reference station software. Phys Chem Earth (A) 26(6–8):545–549
El-Mowafy A (2009) An alternative post-processing relative positioning approach based on precise point positioning. J Surv Eng 135(2):56–65
El-Mowafy A, Teunissen PJG, Odijk D (2010) Single-receiver single-channel real-time validation of GPS, GLONASS, Galileo and COMPASS Data. In: Proceedings of the international symposium on GPS/GNSS, Taipei, Taiwan, 26–28 Oct 2010
Ene A, Blanch J, Powell JD (2007) Fault detection and elimination for Galileo-GPS vertical guidance. In: Proceedings of the Institute of Navigation National Technical Meeting, San Diego, CA, 22–24 Jan 2007
Euler H-J, Goad CC (1991) On optimal filtering of GPS dual-frequency observations without using orbit information. Bull Géodésique 65:130–143
Farrell JL, Van Graas F (1992) Statistical validation for GPS integrity test. Navigation 39(2):205–216
Gelb A (1974) Applied optimal estimation. Massachusetts Institute of Technology Press, Cambridge
Guo J, Lu M, Cui X, Feng Z (2011) A new RAIM algorithm for triple-frequency GNSS receivers. In: Proceedings of the 2011 International Technical Meeting of The Institute of Navigation San Diego, CA, 24–26 Jan 2011, pp 271–278
Kaplan ED (2006) Understanding GPS—principles and applications, 2nd edn. Artech House, Boston
Kim D, Langley RB (2002) Instantaneous real-time cycle-slip correction for quality control of GPS carrier-phase measurements. Navigation 49(4):205–222
Kok J (1984) On data snooping and multiple outlier testing, vol. 30 of NOAA technical report NOS.: NGS, U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Ocean Service, Charting and Geodetic Services
Lee Y (2012) New advanced RAIM with improved availability for detecting constellation-wide faults using two independent constellations. Navigation 60(1):71–83
Leick A (2004) GPS satellite surveying, 3rd edn. Wiley, New York
Neri P, Azoulai L, Macabiau C (2011) Study of the temporal behavior of GPS/GALILEO NSE and RAIM for LPV200. In: Proceedings of the ION GNSS 2011, Oregon, Portland, 19–23 Sept 2011
Teunissen PJG (1990) Quality control in integrated navigation systems. IEEE Aerosp Electron Syst Mag 5(7):35–41
Teunissen PJG (1998) Minimal detectable biases of GPS data. J Geodesy 72:236–244
Teunissen PJG (2006) Testing theory: an introduction, 2nd edn. Delft VSSD, The Netherlands
Teunissen PJG, de Bakker PF (2012) Next generation GNSS single receiver cycle slip reliability. In: Proceedings of VII Hotine-Marussi symposium on mathematical geodesy, international association of geodesy symposia, vol 137, pp 159–164
Teunissen PJG, Kleusberg A (1998) GPS for geodesy, 2nd edn. Springer, NY
Acknowledgments
The author would like to thank Prof. P. J. G. Teunissen for proposing to carry out this study and for his suggestions and comments. The IRG fund received from Curtin University of Technology to carry out this research, project number 47606, is acknowledged.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
El-Mowafy, A. GNSS multi-frequency receiver single-satellite measurement validation method. GPS Solut 18, 553–561 (2014). https://doi.org/10.1007/s10291-013-0352-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10291-013-0352-6