Geração de VRS a partir de modelos atmosféricos: Conceito, implementação e resultados

Nowadays, with the implantation of GNSS (Global Navigation Satellite System) reference station networks, several positioning techniques have been developed and/or improved. Using such kind of network data it is possible to model the GNSS distance dependent errors and to compute correction terms for the network region. Several methods have been developed to formulate the corrections terms from network stations data. A method that has been received a great attention is the Virtual Reference Station (VRS). The idea is that the VRS data resemble as much as possible a real receiver data placed in the same local. Therefore, the user has the possibility of using the VRS as if it were a real reference station in your proximities, and to accomplish the relative positioning with a single frequency receiver. In this paper it is described a different methodology applied to implement the VRS concept, using atmospheric models developed by Brazilian researchers. Besides, experiments for evaluating the quality of generated VRS are presented, showing the efficiency of the proposed method.

Towards forecasting and mitigating ionospheric scintillation effects on GNSS

The effect of the ionosphere on the signals of Global Navigation Satellite Systems (GNSS), such as the Global Positionig System (GPS) and the proposed European Galileo, is dependent on the ionospheric electron density, given by its Total Electron Content (TEC). Ionospheric time-varying density irregularities may cause scintillations, which are fluctuations in phase and amplitude of the signals. Scintillations occur more often at equatorial and high latitudes. They can degrade navigation and positioning accuracy and may cause loss of signal tracking, disrupting safety-critical applications, such as marine navigation and civil aviation. This paper addresses the results of initial research carried out on two fronts that are relevant to GNSS users if they are to counter ionospheric scintillations, i.e. forecasting and mitigating their effects. On the forecasting front, the dynamics of scintillation occurrence were analysed during the severe ionospheric storm that took place on the evening of 30 October 2003, using data from a network of GPS Ionospheric Scintillation and TEC Monitor (GISTM) receivers set up in Northern Europe. Previous results [1] indicated that GPS scintillations in that region can originate from ionospheric plasma structures from the American sector. In this paper we describe experiments that enabled confirmation of those findings. On the mitigation front we used the variance of the output error of the GPS receiver DLL (Delay Locked Loop) to modify the least squares stochastic model applied by an ordinary receiver to compute position. This error was modelled according to [2], as a function of the S4 amplitude scintillation index measured by the GISTM receivers. An improvement of up to 21% in relative positioning accuracy was achieved with this technnique.

Generating VRS data using atmospheric models: How far can we go?

Nowadays, with the expansion of the reference stations networks, several positioning techniques have been developed and/or improved. Among them, the VRS (Virtual Reference Station) concept has been very used. In this paper the goal is to generate VRS data in a modified technique. In the proposed methodology the DD (double difference) ambiguities are not computed. The network correction terms are obtained using only atmospheric (ionospheric and tropospheric) models. In order to carry out the experiments it was used data of five reference stations from the GPS Active Network of West of São Paulo State and an extra station. To evaluate the VRS data quality it was used three different strategies: PPP (Precise Point Positioning) and Relative Positioning in static and kinematic modes, and DGPS (Differential GPS). Furthermore, the VRS data were generated in the position of a real reference station. The results provided by the VRS data agree quite well with those of the real file data.

Spectral analysis and low-frequency multipath mitigation for kinematic applications

Low-frequency multipath is still one of the major challenges for high precision GPS relative positioning. In kinematic applications, mainly, due to geometry changes, the low-frequency multipath is difficult to be removed or modeled. Spectral analysis has a powerful technique to analyze this kind of non-stationary signals: the wavelet transform. However, some processes and specific ways of processing are necessary to work together in order to detect and efficiently mitigate low-frequency multipath. In this paper, these processes are discussed. Some experiments were carried out in a kinematic mode with a controlled and known vehicle movement. The data were collected in the presence of a reflector surface placed close to the vehicle to cause, mainly, low-frequency multipath. From theanalyses realized, the results in terms of double difference residuals and statistical tests showed that the proposed methodology is very efficient to detect and mitigate low-frequency multipath effects. © 2008 IEEE.

An effective wavelet method to detect and mitigate low-frequency multipath effects

To ensure high accuracy results from GPS relative positioning, the multipath effects have to be mitigated. Although the careful selection of antenna site and the use of especial antennas and receivers can minimize multipath, it cannot always be eliminated and frequently the residual multipath disturbance remains as the major error in GPS results. The high-frequency multipath from large delays can be attenuated by double difference (DD) denoising methods. But the low-frequency multipath from short delays is very difficult to be reduced or modeled. In this paper, it is proposed a method based on wavelet regression (WR), which can effectively detect and reduce the low-frequency multipath. The wavelet technique is firstly applied to decompose the DD residuals into the low-frequency bias and high-frequency noise components. The extracted bias components by WR are then directly applied to the DD observations to correct them from the trend. The remaining terms, largely characterized by the high-frequency measurement noise, are expected to give the best linear unbiased solutions from a least-squares (LS) adjustment. An experiment was carried out using objects placed close to the receiver antenna to cause, mainly, low-frequency multipath. The data were collected for two days to verify the multipath repeatability. The ground truth coordinates were computed with data collected in the absence of the reflector objects. The coordinates and ambiguity solution were compared with and without the multipath mitigation using WR. After mitigating the multipath, ambiguity resolution became more reliable and the coordinates were more accurate.

The impact of adding SBAS data on GPS data processing in southeast of Brazil: Preliminary result

Nowadays, L1 SBAS signals can be used in a combined GPS+SBAS data processing. However, such situation restricts the studies over short baselines. Besides of increasing the satellite availability, SBAS satellites orbit configuration is different from that of GPS. In order to analyze how these characteristics can impact GPS positioning in the southeast area of Brazil, experiments involving GPS-only and combined GPS+SBAS data were performed. Solutions using single point and relative positioning were computed to show the impact over satellite geometry, positioning accuracy and short baseline ambiguity resolution. Results showed that the inclusion of SBAS satellites can improve the accuracy of positioning. Nevertheless, the bad quality of the data broadcasted by these satellites limits their usage. © Springer-Verlag Berlin Heidelberg 2012.

Análise de séries temporais de coordenadas estimadas com GPS: uma proposta metodológica para eliminação de efeitos sazonais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise de wavelets para detecção e correção do multicaminho no posicionamento relativo GNSS estático e cinemático

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Investigações sobre o impacto da modernização do GNSS no Posicionamento

Pós-graduação em Ciências Cartográficas - FCT

Solução rápida das ambigüidades GPS para aplicações no posicionamento relativo de linhas de base curtas

Pós-graduação em Ciências Cartográficas - FCT

Posicionamento relativo na região equatorial em diversas condições ionosféricas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Efeito de multicaminho de alta frequência no posicionamento relativo GPS estático: detecção e atenuação utilizando wavelets

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Simulação hidrodinâmica e caracterização experimental de mecanismos anti-sifão em sistemas de drenagem externa de líquido cefalorraquidiano

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Investigações preliminares sobre a influência do clima espacial no posicionamento relativo com GNSS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise de modelos troposféricos no posicionamento baseado em redes usando o conceito de VRS

In the past few years several GPS (Global Position System) positioning techniques have been develope and/or improved with the goal of obtaining high accuracy and productivity in real time. The reference station network concept besides to enabling quality and reliability in positioning for scientific and civil GPS community, allows studies concerning tropospheric refraction modeling in the network region. Moreover, among the network corrections transmission methods available to users, there is the VRS (Virtual Reference Station) concept. In this method, the data of a virtual station are generated near the rover receiver (user). This provides a short baseline and the user has the possibility of using a single frequency receiver to accomplish the relative positioning. In this paper, the methodology applied to generate VRS data, using different tropospheric models is described. Thus, comparative tests were conducted in the four seasons with the NWP/INPE (Numerical Weather Prediction/National Institute for Space Research) and Hopfield tropospheric models. In order to analyse the VRS data quality, it was used the Precise Point Positioning (PPP) method, where satisfactory results were found. Mean differences between PNT/INPE and Hopfield models of 9.75% and 24.2% for the hydrostatic and wet days, respectively were obtained.