Virtual Reference Station Systems

Landau, Herbert; Vollath, Ulrich; Chen, Xiaoming

doi:10.5081/jgps.1.2.137

Cited by 136 publications

(83 citation statements)

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“…• plane triangles (Vollath et al, 2000, Landau et al, 2002; • an Inverse Distance Weighting (IDW) estimation; • least squares method for estimating polynomial coefficients; • collocation . This strategy can also be applied for post-processing positioning, by mean of a virtual data file (usually, in RINEX format).…”

Section: The Vrs Positioningmentioning

confidence: 99%

Achievable Positioning Accuracies in a Network of GNSS Reference Stations

Manzino¹,

Dabove²,

Agostino³

2012

Global Navigation Satellite Systems: Signal, Theory and Applications

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Section: The Vrs Positioningmentioning

confidence: 99%

Achievable Positioning Accuracies in a Network of GNSS Reference Stations

Manzino¹,

Dabove²,

Agostino³

2012

Global Navigation Satellite Systems: Signal, Theory and Applications

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“…network RTK) enables high-precision RTK positioning to be realized for medium-long baselines (typically between 30-150 km), and this technology has been successfully implemented in many experiments (e.g. Chen et al, 2000;Lachapelle et al, 2000;Odijk et al, 2000;Vollath et al, 2000;Raquet and Lachapelle, 2001;Landau et al, 2003;Vollath et al, 2002;Hu et al, 2003;Rizos and Han, 2003;Alves, 2004).…”

Section: Introductionmentioning

confidence: 99%

An improved regularization method for estimating near real-time systematic errors suitable for medium-long GPS baseline solutions

et al. 2008

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It is well known that the key problem associated with network-based real-time kinematic (RTK) positioning is the estimation of systematic errors of GPS observations, such as residual ionospheric delays, tropospheric delays, and orbit errors, particularly for medium-long baselines. Existing methods dealing with these systematic errors are either not applicable for making estimations in real-time or require additional observations in the computation. In both cases, the result is a difficulty in performing rapid positioning. We have developed a new strategy for estimating the systematic errors for near real-time applications. In this approach, only two epochs of observations are used each time to estimate the parameters. In order to overcome severe ill-conditioned problems of the normal equation, the Tikhonov regularization method is used. We suggest that the regularized matrix be constructed by combining the a priori information of the known coordinates of the reference stations, followed by the determination of the corresponding regularized parameter. A series of systematic errors estimation can be obtained using a session of GPS observations, and the new process can assist in resolving the integer ambiguities of medium-long baselines and in constructing the virtual observations for the virtual reference station. A number of tests using three medium-to long-range baselines (from tens of kilometers to longer than 1000 kilometers) are used to validate the new approach. Test results indicate that the coordinates of three baseline lengths derived are in the order of several centimeters after the systematical errors are successfully removed. Our results demonstrate that the proposed method can effectively estimate systematic errors in the near real-time for medium-long GPS baseline solutions.

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“…A review of various multi-reference station network approaches can be found in Fotopoulos and Cannon (2001), Lachapelle and Alves (2002), Rizos (2002) and in the original papers (e.g., Wanninger, 1995;Wübbena et al, 1996;Wanninger, 1997Wanninger, , 1999Wanninger, , 2002Wanninger, , 2004Raquet, 1997Raquet, , 1997Lachapelle et al, 2000;Euler et al, 2001;Landau et al, 2002;Grejner-Brzezińska et al, 2005). The presented models concern mostly carrier-phase positioning where high accuracy is expected, such as in cm or mm.…”

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confidence: 99%

“…This concept, in real-time positioning, is realised by setting up a central computing facility collecting the RS observation data and performing pre-processing to obtain correction models for distance-dependent biases. The user can transmit his approximate position to the central computing facility and by return he receives VRS observations based on the real RS data and the correction models (Euler et al, 2001;Landau et al, 2002). This concept has several advantages and allows observation errors to be reduced by error modelling in the network.…”

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confidence: 99%

Performance Of Static Positioning For Medium Distances Based On Data From A Virtual Reference Station And ASG-PL Network

Bakuła¹

2006

Artificial Satellites

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ABSTRACT:The use of a network of reference stations instead of a single reference station allows the modelling of some systematic errors in a region and allows a user to increase the distance between the rover receiver and reference stations. In some countries, GPS reference stations exist and GPS observations are available for users in real-time mode and in postprocessing. Observations from several GPS reference stations in a regional network enable modelling spatially-correlated errors and their modelling on an epoch-by-epoch and satelliteby-satellite basis. As a result, observations of a virtual reference station can be created at a rover's approximate position and its observations can be used in the precise baseline positioning of the rover. This paper presents the performance of the static positioning of a rover station, its quality and reliability for two different baselines. Single-baseline and network static solutions are presented and compared. Network solutions are based on data from a virtual reference station (VRS) obtained by the Wasoft/Virtuall software. In both cases, the same strategy of ambiguity resolution was used. These approaches have been tested with the use of 24-hour GPS data from the Polish Active Geodetic Network (ASG-PL). The data from three reference stations with medium-range separation were used in the process of generating VRS data. GPS data of the rover station were divided into 20, 10 and 5-min. sessions with a sampling interval of 5 sec. Practical calculations and analyses of horizontal and vertical accuracy of coordinates clearly show the improvement of static positioning in terms of time observation span and ambiguity reliability.

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Virtual Reference Station Systems

Abstract: He has many years of experience in GPS and has been involved in a large variety of GPS and GLONASS developments for high precision positioning systems and applications.

Cited by 136 publications

References 0 publications

Achievable Positioning Accuracies in a Network of GNSS Reference Stations

Achievable Positioning Accuracies in a Network of GNSS Reference Stations

An improved regularization method for estimating near real-time systematic errors suitable for medium-long GPS baseline solutions

Performance Of Static Positioning For Medium Distances Based On Data From A Virtual Reference Station And ASG-PL Network

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