An Overview of Multi-Reference Station Methods for cm-Level Positioning

Fotopoulos, G.; Cannon, M. Elizabeth

doi:10.1007/pl00012849

Cited by 117 publications

(62 citation statements)

References 12 publications

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“…Over the past few years, in order to interpolate (or model) the distance-dependent residual biases, several interpolation methods have been proposed. They include the Linear Combination Model (Han & Rizos, 1996;Han, 1997), the Distance-Based Linear Interpolation Method (Gao & Li, 1998), the Linear Interpolation Method (Wanninger, 1995), the Low-Order Surface Model (Wübbena et al, 1996;Fotopoulos & Cannon, 2001), and the Least Squares Collocation Method (Raquet, 1998;Marel, 1998). The theoretical and numerical comparison of the various interpolation algorithms has been made by Dai et al (2003), and there is no obviously 'superior' technique.…”

Section: Network Rtk Issues: Theoretical and Practical Challengesmentioning

confidence: 99%

Network RTK Research and Implementation: A Geodetic Perspective

Rizos

2002

J. of GPS

141

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Section: Network Rtk Issues: Theoretical and Practical Challengesmentioning

confidence: 99%

Network RTK Research and Implementation: A Geodetic Perspective

Rizos

2002

J. of GPS

141

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“…A commonly used spatial interpolation methods for modeling the ionospheric refraction and geometric errors may be divided into two groups (Al-Shaery et al, 2011): (i) the deterministic methods (e.g. Distance-Based Linear Interpolation Method (Gao et al, 1997), Linear Combination Model (Han andRizos, 1996, 1997), Linear Interpolation Method (Wanninger, 1995), Low-Order Surface Model (Fotopoulos and Cannon, 2001)) and (ii) the geostatistical methods (e.g. Least-Squares Collocation Method (Marel, 1998;Raquet, 1998), Ordinary Kriging Method (Wielgosz et al, 2003;Al-Shaery et al, 2011)).…”

Section: Application Parameters and Solution Algorithmmentioning

confidence: 99%

Study on the influence of stochastic properties of correction terms on the reliability of instantaneous network RTK

Próchniewicz

2014

Artificial Satellites

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ABSTRACT. The reliability of precision GNSS positioning primarily depends on correct carrier-phase ambiguity resolution. An optimal estimation and correct validation of ambiguities necessitates a proper definition of mathematical positioning model. Of particular importance in the model definition is the taking into account of the atmospheric errors (ionospheric and tropospheric refraction) as well as orbital errors. The use of the network of reference stations in kinematic positioning, known as Network-based Real-Time Kinematic (Network RTK) solution, facilitates the modeling of such errors and their incorporation, in the form of correction terms, into the functional description of positioning model. Lowered accuracy of corrections, especially during atmospheric disturbances, results in the occurrence of unaccounted biases, the so-called residual errors. The taking into account of such errors in Network RTK positioning model is possible by incorporating the accuracy characteristics of the correction terms into the stochastic model of observations. In this paper we investigate the impact of the expansion of the stochastic model to include correction term variances on the reliability of the model solution. In particular the results of instantaneous solution that only utilizes a single epoch of GPS observations, is analyzed. Such a solution mode due to the low number of degrees of freedom is very sensitive to an inappropriate mathematical model definition. Thus the high level of the solution reliability is very difficult to achieve. Numerical tests performed for a test network located in mountain area during ionospheric disturbances allows to verify the described method for the poor measurement conditions. The results of the ambiguity resolution as well as the rover positioning accuracy shows that the proposed method of stochastic modeling can increase the reliability of instantaneous Network RTK performance.

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“…Varner, 2000, Fotopoulos and Cannon, 2001and Wübbena and Bagge, 2002. An example is given by the latter study for generation of FKP, where the errors are computed as follows:…”

Section: The Area-parameter Corrections-flächenkorrekturparameter (Fkmentioning

confidence: 99%

Precise Real-Time Positioning Using Network RTK

El‐Mowafy¹

2012

Global Navigation Satellite Systems: Signal, Theory and Applications

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An Overview of Multi-Reference Station Methods for cm-Level Positioning

Cited by 117 publications

References 12 publications

Network RTK Research and Implementation: A Geodetic Perspective

Network RTK Research and Implementation: A Geodetic Perspective

Study on the influence of stochastic properties of correction terms on the reliability of instantaneous network RTK

Precise Real-Time Positioning Using Network RTK

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