Musa, Tajul A and Wang, Jinling and Rizos, Chris (2004) A stochastic modelling method for network-based GPS positioning. In: European Navigation Conference on Global Navigation Satellite System 2004 (ENC-GNSS04), 16-19 May 2004, Rotterdam, The Netherlands.
Over the past few years the network-based GPS surveying technique has been widely discussed. The main advantage of the network-based technique is that the distance-dependent errors (i.e, residual atmospheric biases and orbit error effects) can be reduced and the performance of conventional single reference station, carrier phase-based techniques can be extended over longer baselines. However, even though the errors can largely be reduced by such network techniques, in practice the positioning performance is still affected by the residual biases due to imperfect network functional models. The residual biases contribute to the noise terms and it is difficult to define a functional model that can deal with them. An alternative approach is to account for these residual biases (and observation noise) within the stochastic model. In this study, a network stochastic model estimated from least squares residuals is proposed to account for residual systematic errors. Using a two-stage approach, the network measurements are transformed into a new set of measurements which are largely free of temporal correlations. The variance-covariance matrix of the transformed measurements can be estimated using a rigorous statistical method. The analysis of residual time series shows that more realistic positioning results can be obtained with the proposed network stochastic model. This paper will describe the proposed stochastic modelling method for the network-based GPS positioning, and will include the presentation of encouraging experimental results.
|Item Type:||Conference or Workshop Item (Paper)|
|Uncontrolled Keywords:||Network-Based Positioning, Stochastic Modelling, GPS|
|Subjects:||T Technology > TA Engineering (General). Civil engineering (General)|
|Divisions:||Geoinformation Science And Engineering (Formerly known)|
|Deposited By:||En. Tajul Ariffin Musa|
|Deposited On:||01 Mar 2007 02:59|
|Last Modified:||22 Dec 2011 05:15|
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