Abstract
The receiver autonomous integrity monitoring (RAIM) is the straightforward way to handle the outlier, but the protection levels are vulnerable to the satellite geometry. A robust protection level is proposed. Firstly, a robust positioning solution based on MM-estimation is introduced. Then the protection level of the robust solution is presented. Finally, the experiments with actual GPS data demonstrate that the robust protection levels are less affected by the geometry. Moreover, the robust protection levels are more stringent to bound the maximum error than the conventional protection levels.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Graas FV, Farrell JL (1992) Baseline fault detection and exclusion algorithm. In: Proceedings of the annual meeting—institute of navigation, pp 413–420
Brown RG (1992) A baseline GPS RAIM scheme and a note on the equivalence of three RAIM methods. Navig J Inst Navig 39(3):301–316
Walter T, Enge P, Blanch J, Pervan B (2008) Worldwide vertical guidance of aircraft based on modernized GPS and new integrity augmentations. Proc IEEE 96(12):1918–1935
Angus JE (2006) RAIM with multiple faults. Navig J Inst Navig 53(4):249–257
Milner CD (2009) Weighted RAIM for APV: an optimised protection level. In: ION GNSS 22nd international meeting of the satellite division, pp 1646–1652
Bruckner D, Graas FV, Skidmore T (2011) Approximations to composite GPS protection levels for aircraft precision approach and landing. GPS Solut 15(4):333–344
Phase II of the GNSS evolutionary architecture study. Technical report, GEAS Panel (2010)
Huber P (1981) Robust statistics. Wiley, New York
Hampel F, Ronchetti E, Rousseeuw P, Stahel W (1986) Robust statistics: the approach based on influence functions. Wiley, New York
Rousseeuw PJ, Leroy AM (1987) Robust regression and outlier detection. Wiley, New York
Yohai VJ (1987) High breakdown point and high efficiency robust estimates for regression. Ann Stat 15(2):642–656
Gervini D, Yohai VJ (2002) A class of robust and fully efficient regression estimators. Ann Stat 30(2):583–616
Berrendero JR, Mendes BVM, Tyler DE (2007) On the maximum bias functions of MM-estimates and constrained M-estimates of regression. Ann Stat 35(1):13–40
Wieser A, Fritz KB (2002) Short static GPS sessions: robust estimation results. GPS Solut 5(3):70–79
Yang Y, Song L, Xu T (2002) Robust estimator for correlated observations based on bifactor equivalent weights. J Geodesy 76:353–358
Chang XW, Guo Y (2005) Huber’s M-estimation in relative GPS positioning: computational aspects. J Geodesy 79:351–362
Yang Y, He H, Xu G (2001) Adaptively robust filtering for kinematic geodetic positioning. J Geodesy 75:109–116
Wang J, Wang J (2007) Mitigating the effect of multiple outliers on GNSS navigation with M-estimation schemes. In: IGNSS symposium 2007, pp 1–9
Knight NL, Wang J (2009) A comparison of outlier detection procedures and robust estimation methods in GPS positioning. J Navig 62:699–709
Maronna RA, Martin RD, Yohai VJ (2006) Robust statistics theory and method. Wiley, Chichester
Tong H-B, Zhang G-Z, Ou G (2012) Iterative reweighted recursive least squares for robust positioning. Electron Lett 48(13):789–791
Walter T, Enge P (1995) Weighted RAIM for precision approach. In: ION GPS, pp 1995–2004
Tong H, Zhang G, Ou G (2011) GNSS RAIM availability assessment for worldwide precision approaches. In: 2011 International workshop on multi-platform/multi-sensor remote sensing and mapping (M2RSM), pp 1–4
Do J (2012) GPS/GNSS matlab platform. http://waas.stanford.edu/sgmp/sgmp.htm. Accessed 1 May 2012
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tong, H., Peng, J., Zhang, G., Ou, G. (2013). GNSS Integrity Monitoring Based on the Robust Positioning Solution. In: Lu, W., Cai, G., Liu, W., Xing, W. (eds) Proceedings of the 2012 International Conference on Information Technology and Software Engineering. Lecture Notes in Electrical Engineering, vol 211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34522-7_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-34522-7_3
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34521-0
Online ISBN: 978-3-642-34522-7
eBook Packages: EngineeringEngineering (R0)