Abstract
The reliability and performance of GPS receivers depend on the quality of the signal received, which can be largely affected by the interference caused by buildings, trees, and other obstacles. Since obstacles are always present in practical applications, several statistical representations have been developed along the years to measure, predict, and compensate errors induced by interferences. Two of the most used models to characterize GPS signal fading are the Nakagami-m and Rice, but in this work, we present evidence that supports the κ–μ distribution as the best fit to deal with multifrequency GPS multipath channels inside urban, rural, and forest areas. A synthetic signal simulator was developed to create propagation cases involving scattering clusters and specular reflections. Additionally, experimental measurements are presented to confirm the κ–μ distribution as the best distribution to characterize different situations on the available three GPS frequencies. We then present typical values of fading coefficients in L1, L2C, and L5 signals, for cases involving urban canyons, regular urban, rural, and dense vegetation areas. These coefficients can also be used to evaluate the receiver performance under similar cases or may be applied in weights measurement methods for positioning computation improvement.
Similar content being viewed by others
Data availability
Data may be considered for sharing upon request at https://zenodo.org/record/4037384#.X2fPd9R7m00.
References
Abbas SA, Sheikh AU (1996) A geometric theory of Nakagami fading multipath mobile radio channel with physical interpretations. In: Proceedings of vehicular technology conference-VTC, Apr 28, pp 637–641. https://doi.org/10.1109/vetec.1996.501389
Cardieri P (2010) Modeling interference in wireless Ad Hoc networks. IEEE Commun Surv Tutor 12(4):551–572. https://doi.org/10.1109/SURV.2010.032710.00096
Coleman TF, Li Y (1994) On the convergence of interior-reflective Newton methods for nonlinear minimization subject to bounds. Math Program 67(1–3):189–224. https://doi.org/10.1007/BF01582221
Coleman TF, Li Y (1996) An interior trust region approach for nonlinear minimization subject to bounds. SIAM J Optim 6(2):418–445. https://doi.org/10.1137/0806023
Cotton SL, Scanlon WG (2009) Channel characterization for single- and multiple-antenna wearable systems used for indoor body-to-body communications. IEEE Trans Antennas Propag 57(4):980–990. https://doi.org/10.1109/TAP.2009.2014576
Gaertner G, Nuallain EO (2007) Characterizing wideband signal envelope fading in urban microcells using the Rice and Nakagami distributions. IEEE Trans Veh Technol 56(6):3621–3630. https://doi.org/10.1109/TVT.2007.901857
Håkansson M (2019) Characterization of GNSS observations from a Nexus 9 Android tablet. GPS Solut 23(1):21. https://doi.org/10.1007/s10291-018-0818-7
Lehner A, Steingass A (2005) A novel channel model for land mobile satellite navigation. In: Proceedings of ION GNSS 2005 Institute of Navigation, Long Beach, California, USA, September 13–16, pp 2132–2138
Lee WC (2010) Mobile communications design fundamentals. John Wiley & Sons
Li F, Wang Y (2007) Routing in vehicular ad hoc networks: A survey. IEEE Vehicular technology magazine 2(2):12–22
Marcum J (1960) A statistical theory of target detection by pulsed radar. IRE Trans Inf Theory 6(2):59–267
Moraes AO, Costa E, de Paula ER, Perrella WJ, Monico JFG (2014) Extended ionospheric amplitude scintillation model for GPS receivers. Radio Sci 49(5):315–329. https://doi.org/10.1002/2013RS005307
Moraes AO, Vani BC, Costa E, Abdu MA, de Paula ER, Sousasantos J, Galera Monico JF, Forte B, de Siqueira Negreti PM, Shimabukuro MH (2018) GPS availability and positioning issues when the signal paths are aligned with ionospheric plasma bubbles. GPS Solut 22(4):95. https://doi.org/10.1007/s10291-018-0760-8
Moraes A, Sousasantos J, de Paula ER, Pereira da Cunha JJP, Lima Filho VC, Vani BC (2019) Performance analysis of κ–μ distribution for Global Positioning System (GPS) L1 frequency-related ionospheric fading channels. J Space Weather Space Clim 9:A15. https://doi.org/10.1051/swsc/2019012
Pérez Fontán F, Mariño Espiñeira P (2008) Modelling the wireless propagation channel: a simulation approach with MATLAB. Wiley, Hoboken
Simon MK, Alouini MS (2005) Digital communication over fading channels, 2nd edn. Wiley, Hoboken
Strode PRR, Groves PD (2016) GNSS multipath detection using three-frequency signal-to-noise measurements. GPS Solut 20(3):399–412. https://doi.org/10.1007/s10291-015-0449-1
Veettil SV, Aquino M, Marques HA, Moraes A (2020) Mitigation of ionospheric scintillation effects on GNSS precise point positioning (PPP) at low latitudes. J Geodesy 94(2):1–10. https://doi.org/10.1007/s00190-020-01345-z
Yacoub MD (2007) The κ–μ distribution and the η–μ distribution. IEEE Antennas Propag Mag 49(1):68–81. https://doi.org/10.1109/MAP.2007.370983
Zhang X, Tao X, Zhu F et al (2018) Quality assessment of GNSS observations from an Android N smartphone and positioning performance analysis using time-differenced filtering approach. GPS Solut 22(3):70. https://doi.org/10.1007/s10291-018-0736-8
Acknowledgements
VCLF conducted this research in the framework of the INCT GNSS-NavAer project under Grants CNPq (465648/2014-2) and FAPESP (2017/50115-0). AOM is grateful to CNPq Award Number 314043/2018-7.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Lima Filho, V.C., Moraes, A. Modeling multifrequency GPS multipath fading in land vehicle environments. GPS Solut 25, 3 (2021). https://doi.org/10.1007/s10291-020-01040-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10291-020-01040-8