Developing a position estimation algorithmin GNSS-Precise Point Positioning technique depending on Extended Kalman Filter


Abstract in English

Precise point positioning technique uses recursive algorithms to solve the navigation problem. In fact, traditional least square method doesn’t meet the requiredassessments of processing speed, and quality in different geodetic and surveying applications,due tobig amount of output processing data provided by global navigation satellite systems. Extended Kalman filter is considered as optimal solution approach of the navigation problem. This filter requiresthe knowledge of measurements, its observational models, and physical state for estimation problem like: (receiver dynamic, received signals characters, and suitable estimation of its initial conditions). Research refers to a mathematical suggestion, which reduce the negative effect of convergence time at EKF initial conditions. This work also shows how a position estimation accuracy affected by the suggested modification of using EKF in PPP, and supporting the use ofthis modification in position estimation field, in spite of increasing processing time.

References used

MARTIN, I.GNSS Precise Point Positioning:The enhancement with GLONASS. School of Civil Engineering and Geosciences Newcastle University, Newcastle, 2013, 244
MARTÍN, A.; ANQUELA, A.B.; CAPILLA, R.; BERNÉ, J. L.PPP Technique Analysis Based On Time Convergence, Repeatability, IGS Products, Different Software Processing And GPS+Glonass Constellation. Journal Of Surveying Engineering, Vol.137, NO. 3, 2011, 99-108
LE, A.;TEUNISSEN, P. Optimal Recursive Least-Squares Filtering Of GPS Pseudorange Measurements. Springer, Verlag, 2008,540

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