Precise Point Positioning (PPP) is a wellknown technique of positioning by Global Navigation Satellite Systems (GNSS) that provides accurate solutions. With the availability of real-time precise orbit and clock products provided by the International GNSS Service (IGS) and by individual analysis centers such as Centre National d'Etudes Spatiales through the IGS Real-Time Project, PPP in real time is achievable. With such orbit and clock products and using dual-frequency receivers, first-order ionospheric effects can be eliminated by the ionospheric-free combination. Concerning the tropospheric delays, the Zenith Hydrostatic Delays can be quite well modeled, although the Zenith Wet Delays (ZWDs) have to be estimated because they cannot be mitigated by, for instance, observable combinations. However, adding ZWD estimates in PPP processing increases the time to achieve accurate positions. In order to reduce this convergence time, we (1) model the behavior of troposphere over France using ZWD estimates at Orphéon GNSS reference network stations and (2) send the modeling parameters to the GNSS users to be introduced as a priori ZWDs, with an appropriate uncertainty. At the user level, float PPP-RTK is achieved; that is, GNSS data are performed in kinematic mode and ambiguities are kept float. The quality of the modeling is assessed by comparison with tropospheric products published by Institut National de l'Information Géographique et Forestière. Finally, the improvements in terms of required time to achieve 10-cm accuracy for the rover position (simulated float PPP-RTK) are quantified and discussed. Results for 68 % quantiles of absolute errors convergence show that gains for GPS-only positioning with ZWDs derived from the assessed tropospheric modeling are about: 1 % (East), 20 % (North), and 5 % (Up). Since ZWD estimation is correlated with satellite geometry, we also investigated the positioning when processing GPS ? GLONASS data, which increases significantly the number of available satellites. The improvements achieved by adding tropospheric corrections in this case are about: 2 % (East), 5 % (North), and 13 % (Up). Finally, a reduction in the number of reference stations by using a sparser network configuration to perform the tropospheric modeling does not degrade the generated tropospheric corrections, and similar performances are achieved.

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O posicionamento em tempo real por meio do emprego dos sinais de satélites foi um avanço nas navegações aérea, marítima e terrestre com o surgimento do GPS (Global Positioning System). Contudo as precisões horizontais e verticais de 100 m e 150 m (nível de probabilidade de 95%) alcançadas, estando a SA (Selective Availability) ativada, passaram a não ser satisfatórias para muitas aplicações e os usuários buscaram galgar outros níveis de precisões. Esforços foram investidos no chamado posicionamento diferencial DGPS (Differential GPS), o qual possibilitou obter precisões em torno de dez vezes melhores do que as do posicionamento absoluto.  Posteriormente, usando-se a fase da onda portadora, conseguiu-se realizar posicionamento com maior acurácia por meio do método RTK (Real Time Kinematic), atingindo qualidade centimétrica. Na sequência, houve uma evolução para posicionamentos em rede, empregando, por exemplo, o algoritmo de VRS (Virtual Reference Station). Vários erros nas observáveis dos satélites passaram a ser modelados com uma solução de multiestações em tempo real. A partir de 2012, surgiram serviços e produtos que favoreceram o desenvolvimento do RT-PPP (Real-Time Precise Point Positioning) baseado no conceito SSR (State Space Representation). A busca da solução das ambiguidades no RT-PPP deu origem ao PPP-RTK com menor tempo de fixação das ambiguidades e convergência para a solução acurada do posicionamento. Neste artigo apresenta-se como foi a evolução do posicionamento em tempo real, algumas das aplicações no âmbito nacional e as perspectivas  desta modalidade de posicionamento para o futuro.

Sou cria de todas as crises que meus 99 anos viveram." (Edgar Morin)Ler o mais recente livro de Edgar Morin que aborda a humanidade diante da pandemia da Covid-19 é ver-se como um agente desse evento histórico e mundial tão presente em nossas vidas. É impossível esquecer-se de que estamos vivendo uma pandemia: o número crescente de mortos, avanços e retrocessos das vacinas, o protocolo de saúde e segurança, bem como as tentativas de boicote a campanhas de prevenção e de vacinação, minimizando os efeitos do vírus letal.

In the Global Navigation Satellite System (GNSS), ambiguity resolution (AR) can shorten observation time and increase the positioning quality. The correct tropospheric modeling is intrinsically related to the ability to perform AR. Here, we assessed the influence of different tropospheric correction alternatives on AR for static Precise Point Positioning (PPP) in Brazilian territory. Our goal was to provide directions to users when choosing a suitable tropospheric model for application in PPP-AR under Brazilian atmospheric conditions. Thus, this study was carried out using well-known models such as the Saastamoinen model and the Zenith Tropospheric Delay (ZTD) Estimation and Numerical Weather Prediction (NWP) model from CPTEC/INPE. Six GNSS stations from the Brazilian Network for Continuous Monitoring (RBMC) (BRAZ, UFPR, RNNA, POVE, SMAR, and SAGA) were selected. Different GNSS processing setups were considered for GNSS data registered at selected stations during summer and winter. The assessment was based on a statistical analysis of positioning accuracy during one-hour sessions. The results indicated that such as the ZTD Estimation, the NWP model provides an accuracy of a few centimeters. On the other hand, the Saastamoinen model provided decimeter level accuracy, thus it is not the recommended choice for PPP-AR in the experimental conditions.