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A New Approach for Optimising GNSS Positioning Performance in Harsh Observation Environments

Published online by Cambridge University Press:  21 July 2014

Shuguo Pan ,
Xiaolin Meng ,
Wang Gao ,
Shengli Wang  and
Alan Dodson
Shuguo Pan*
Affiliation:
(School of Instrument Science and Engineering, Southeast University, Nanjing, China)
Xiaolin Meng
Affiliation:
(Nottingham Geospatial Institute, the University of Nottingham, Nottingham, UK)
Wang Gao
Affiliation:
(School of Transportation, Southeast University, Nanjing, China)
Shengli Wang
Affiliation:
(School of Instrument Science and Engineering, Southeast University, Nanjing, China) (School of Surveying and Mapping Engineering, Anhui University of Science & Technology, Huainan, China)
Alan Dodson
Affiliation:
(Nottingham Geospatial Institute, the University of Nottingham, Nottingham, UK)
*
(E-mail: [email protected])
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Abstract

Maintaining good positioning performance has always been a challenging task for Global Navigation Satellite Systems (GNSS) applications in partially obstructed environments. A method that can optimise positioning performance in harsh environments is proposed. Using a carrier double-difference (DD) model, the influence of the satellite-pair geometry on the correlation among different equations has been researched. This addresses the critical relationship between DD equations and its ill-posedness. From analysing the collected multi-constellation observations, a strong correlation between the condition number and the positioning standard deviation is detected as the correlation coefficient is larger than 0·92. Based on this finding, a new method for determining the reference satellites by using the minimum condition number rather than the maximum elevation is proposed. This reduces the ill-posedness of the co-factor matrix, which improves the single-epoch positioning solution with a fixed DD ambiguity. Finally, evaluation trials are carried out by masking some satellites to simulate common satellite obstruction scenarios including azimuth shielding, elevation shielding and strip shielding. Results indicate the proposed approach improves the positioning stability with multi-constellation satellites notably in harsh environments.

Keywords

Harsh EnvironmentMulti-constellation GNSSObservation StructureCondition NumberReference satellite
Type
Research Article
Information
The Journal of Navigation , Volume 67 , Issue 6 , November 2014 , pp. 1029 - 1048
Copyright
Copyright © The Royal Institute of Navigation 2014 

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References

REFERENCES

Borre, K., and Strang, G. (1997). Linear Algebra Geodesy and GPS. Wellesley-Cambridge Press, USA, pp. 461.Google Scholar
Chang, T.H., Wang, L.S. and Chang, F.R. (2009). A solution to the ill-conditioned GPS positioning problem in an urban environment. Intelligent Transportation Systems, IEEE Transactions on, 10(1), 135–145.Google Scholar
Cline, A.K., Moler, C.B., Stewart, G.W. and Wilkinson, J.H. (1979). An estimate for the condition number of a matrix. SIAM Journal on Numerical Analysis, 16(2), 368–375.Google Scholar
DeLoach, S.R. (1989). Continuous deformation monitoring with GPS. Journal of Surveying Engineering, 115(1), 93–110.Google Scholar
Farooq, M. and Salhi, A. (2011). Improving the solvability of ill-conditioned systems of linear equations by reducing the condition number of their matrices. Journal of the Korean Mathematical Society, 48(5), 939–952.Google Scholar
Ge, M., Gendt, G., Dick, G. and Zhang, F.P. (2005). Improving carrier-phase ambiguity resolution in global GPS network solutions. Journal of Geodesy, 79(1–3), 103–110.CrossRefGoogle Scholar
Ge, M., Gendt, G., Rothacher, M., Shi, C. and Liu, J. (2008). Resolution of GPS carrier-phase ambiguities in precise point positioning (PPP) with daily observations. Journal of Geodesy, 82(7), 389–399.Google Scholar
Gendt, G., Dick, G., Reigber, C.H., Tomassini, M., Liu, Y. and Ramatschi, M. (2003). Demonstration of NRT GPS water vapor monitoring for numerical weather prediction in Germany. Journal of the Royal Meteorological Society, 82(1B), 360–370.Google Scholar
Glonass, I.C.D. (2002). GLONASS ICD. Russian Space Agency, Version, 5, 2002.Google Scholar
Hansen, P.C. (1992). Analysis of discrete ill-posed problems by means of the L-curve. SIAM review, 34(4), 561–580.Google Scholar
Hoque, M.M. and Jakowski, N. (2007). Higher order ionospheric effects in precise GNSS positioning. Journal of Geodesy, 81(4), 259–268.Google Scholar
Huang, D.W., Dai, W.J. and Luo, F.X. (2012). ICA Spatiotemporal Filtering Method and Its Application in GPS Deformation Monitoring. Applied Mechanics and Materials, 204, 2806–2812.Google Scholar
Li, B., Shen, Y. and Feng, Y. (2010). Fast GNSS ambiguity resolution as an ill-posed problem. Journal of Geodesy, 84(11), 683–698.CrossRefGoogle Scholar
Li, L. and Kuhlmann, H. (2012). Real-time deformation measurements using time series of GPS coordinates processed by Kalman filter with shaping filter. Survey Review, 44(326), 189–197.Google Scholar
Loyer, S., Perosanz, F., Mercier, F., Capdeville, H. and Marty, J.C. (2012). Zero-difference GPS ambiguity resolution at CNES–CLS IGS Analysis Center. Journal of Geodesy, 86(11), 991–1003.Google Scholar
Meng, X. (2013). From Structural Health Monitoring to Geo-Hazard Early Warning: An Integrated Approach Using GNSS Positioning Technology. In Earth Observation of Global Changes (EOGC) (pp. 285–293). Springer Berlin Heidelberg.Google Scholar
Meng, X., Roberts, G.W., Dodson, A.H., Cosser, E., Barnes, J. and Rizos, C. (2004). Impact of GPS satellite and pseudolite geometry on structural deformation monitoring: analytical and empirical studies. Journal of Geodesy, 77(12), 809–822.Google Scholar
Mikhail, E.M. and Ackermann, F.E. (1976). Observations and least squares (333–359). New York: IEP.Google Scholar
Pratt, M., Burke, B. and Misra, P. (1998, September). Single-epoch integer ambiguity resolution with GPS-GLONASS L1-L2 Data. In Proceedings of ION GPS, 11, 389–398.Google Scholar
Shen, Y.Z. and Li, B.F. (2007). Regularized solution to fast GPS ambiguity resolution. Journal of Surveying Engineering, 133(4), 168–172.Google Scholar
Takasu, T. and Yasuda, A. (2008). Evaluation of RTK-GPS performance with low-cost single-frequency GPS receivers. In Proceedings of international symposium on GPS/GNSS (pp. 852–861).Google Scholar
Theiss, A., Yen, D.C. and Ku, C.Y. (2005). Global Positioning Systems: an analysis of applications, current development and future implementations. Computer Standards & Interfaces, 27(2), 89–100.Google Scholar
Walsh, D. and Daly, P. (1996). GPS and GLONASS carrier phase ambiguity resolution. In Proceedings of the 9th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 1996) (899–907).Google Scholar
Wang, J. (2000). An approach to GLONASS ambiguity resolution. Journal of Geodesy, 74(5), 421–430.Google Scholar
Wang, J., Stewart, M.P. and Tsakiri, M. (1998). Stochastic modeling for static GPS baseline data processing. Journal of Surveying Engineering, 124(4), 171–181.Google Scholar
Wang, Z., Rizos, C. and Lim, S. (2006). Single epoch algorithm based on Tikhonov regularization for deformation monitoring using single frequency GPS receivers. Survey Review, 38(302), 682–688.CrossRefGoogle Scholar
Wanninger, L. (2012). Carrier-phase inter-frequency biases of GLONASS receivers. Journal of Geodesy, 86(2), 139–148.Google Scholar
Wen, D., Wang, Y. and Norman, R. (2012). A new two-step algorithm for ionospheric tomography solution. GPS solutions, 16(1), 89–94.Google Scholar
Wing, M.G., Eklund, A. and Kellogg, L.D. (2005). Consumer-grade global positioning system (GPS) accuracy and reliability. Journal of Forestry, 103(4), 169–173.Google Scholar
Yang, Y., Li, J., Xu, J., Tang, J., Guo, H. and He, H. (2011). Contribution of the compass satellite navigation system to global PNT users. Chinese Science Bulletin, 56(26), 2813–2819.Google Scholar
Yang, Y.X., He, H.B. and Xu, G. C. (2001). Adaptively robust filtering for kinematic geodetic positioning. Journal of Geodesy, 75(2–3), 109–116.Google Scholar
Yetkin, M. and Berber, M. (2012). Application of the Sign-Constrained Robust Least-Squares Method to Surveying Networks. Journal of Surveying Engineering, 139(1), 59–65.Google Scholar
Yuan, D., Cui, X., Fan, D., Feng, W. and Yu, Y. (2010, March). Application of Kalman Filter Method to the Date Processing of GPS Deformation Monitoring. In Education Technology and Computer Science (ETCS), 2010 Second International Workshop on (Vol. 2, 269–272). IEEE.Google Scholar