HR: 15:15h
AN: A53C-06    [Abstracts]
TI: ZTD Dynamic Modeling Versus Hopfield Model: Evaluation in DGPS Positioning
AU: * Dalbelo, L F
EM: lfdalbelo@gmail.com
AF: Sao Paulo State University, Roberto Simonsen, 305, Presidente Prudente, SP , Brazil
AU: Alves, D B
EM: danibarroca@yahoo.com.br
AF: Sao Paulo State University, Roberto Simonsen, 305, Presidente Prudente, SP , Brazil
AU: Monico, J F
EM: galera@fct.unesp.br
AF: Sao Paulo State University, Roberto Simonsen, 305, Presidente Prudente, SP , Brazil
AU: Sapucci, L F
EM: lsapucci@cptec.inpe.br
AF: CPTEC-INPE, Rodovia Presidente Dutra, Km 40, Cachoeira Paulista, SP , Brazil
AB: A positioning technique that has been received a great attention in the last years it is the Differential GPS (DGPS). This method has been used in several applications such as: navigation, surveying, precision agriculture and others. In the basic concept of DGPS it is assumed a high correlation of errors involved between base and rover stations, considering that the two stations are close together. This way, it is possible to generate corrections for the pseudorange. DGPS provides a reasonable accuracy for short baselines, which is degraded with distance growth due to spatial decorrelation of the errors (ionosphere effect, troposphere refraction and satellites orbit errors), consequently, the method efficiency is reduced. Therefore, to obtain a better positioning quality, an adequate modeling of these errors is indispensable. The aim of this paper is to evaluate the performance of the Numerical Weather Prediction (NWP) model, denominated here dynamic modeling, and the Hopfield empirical model for reducing Zenithal Tropospheric Delay (ZTD) in the DGPS context. The dynamic modeling used is from Center for Weather Forecasting and Climate Studies of the National Institute for Space Research (CPTEC/INPE), which has operationally available ZTD prediction for South American region (available in: http:satelite.cptec.inpe.br/htmldocs/ztd/zenital.htm). Some experiments were carried out using an in-house software developed at FCT/UNESP and data of different GPS baselines lengths: 75, 165, 237 and 443 km. The stations used are from RBMC (Brazilian Continuous Network of Monitoring GPS Satellites) (PPTE, PARA stations) and from GPS Active Network of West of São Paulo State (SEM2, OURI, ROSA stations). The station SEM2 was considered base station. The stations PPTE, OURI, ROSA and PARA were considered rovers. It was processed 2 days of data, December 29 and 30, 2007. The improvement obtained in DGPS using dynamic modeling for the 75, 165, 237 and 443 km baseline was on average 0.35%, 3%, 2.8% and 12.1%, respectively, for the two days in relation to the Hopfield model. These results show that in all evaluated baseline the dynamic modeling has been improved the results if compared with Hopfield empirical model. It is important to verify that with the baseline growth the improvement was very significant.
DE: 1220 Atmosphere monitoring with geodetic techniques (6952)
DE: 1241 Satellite geodesy: technical issues (6994, 7969)
DE: 1610 Atmosphere (0315, 0325)
DE: 3238 Prediction (3245, 4263)
DE: 7959 Models
SC: Atmospheric Sciences [A]
MN: 2007 Joint Assembly