scholarly journals Ambiguity of Residual Constraint-Based Precise Point Positioning with Partial Ambiguity Resolution under No Real-Time Network Corrections Using Real Global Positioning System (GPS) Data

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3220
Author(s):  
Honglei Qin ◽  
Peng Liu ◽  
Li Cong ◽  
Xia Xue
Keyword(s):  
Real Time ◽  
Global Positioning System ◽  
Ambiguity Resolution ◽  
Precise Point Positioning ◽  
Convergence Time ◽  
Positioning System ◽  
Post Processing ◽  
Partial Ambiguity Resolution ◽  
Global Positioning ◽  
Point Positioning

Although precise point positioning (PPP) is a well-established and promising technique with the use of precise satellite orbit and clock products, it costs a long convergence time to reach a centimeter-level positioning accuracy. The PPP with ambiguity resolution (PPP-AR) technique can improve convergence performance by resolving ambiguities after separating the fractional cycle bias (FCB). Now the FCB estimation is mainly realized by the regional or global operating reference station network. However, it does not work well in the areas where network resources are scarce. The contribution of this paper is to realize an ambiguity residual constraint-based PPP with partial ambiguity resolution (PPP-PARC) under no real-time network corrections to speed up the convergence, especially when the performance of the float solution is poor. More specifically, the update strategy of FCB estimation in a stand-alone receiver is proposed to realize the PPP-PAR. Thereafter, the solving process of FCB in a stand-alone receiver is summarized. Meanwhile, the influencing factors of the ambiguity success rate in the PPP-PAR without network corrections are analyzed. Meanwhile, the ambiguity residual constraint is added to adapt the particularity of the partial ambiguity-fixing without network corrections. Moreover, the positioning experiments with raw observation data at the Global Positioning System (GPS) globally distributed reference stations are conducted to determine the ambiguity residual threshold for post-processing and real-time scenarios. Finally, the positioning performance was verified by 22 GPS reference stations. The results show that convergence time is reduced by 15.8% and 26.4% in post-processing and real-time scenarios, respectively, when the float solution is unstable, compared with PPP using a float solution. However, if the float solution is stable, the PPP-PARC method has performance similar to the float solution. The method shows the significance of the PPP-PARC for future PPP applications in areas where network resource is deficient.

Subsidence is determined in the heart of the Central Valley using Post Processed Static and Precise Point Positioning techniques

2020 ◽  
Vol 14 (1) ◽  
pp. 113-118 ◽  
Author(s):  
Y. Facio ◽  
M. Berber
Keyword(s):  
Data Processing ◽  
Global Positioning System ◽  
Precise Point Positioning ◽  
Central Valley ◽  
Gps Data ◽  
Positioning System ◽  
Online Services ◽  
Global Positioning ◽  
System Data ◽  
Point Positioning

AbstractPost Processed Static (PPS) and Precise Point Positioning (PPP) techniques are not new; however, they have been refined over the decades. As such, today these techniques are offered online via GPS (Global Positioning System) data processing services. In this study, one Post Processed Static (OPUS) and one Precise Point Positioning (CSRS-PPP) technique is used to process 24 h GPS data for a CORS (Continuously Operating Reference Stations) station (P565) duration of year 2016. By analyzing the results sent by these two online services, subsidence is determined for the location of CORS station, P565, as 3–4 cm for the entire year of 2016. In addition, precision of these two techniques is determined as ∼2 cm. Accuracy of PPS and PPP results is 0.46 cm and 1.21 cm, respectively. Additionally, these two techniques are compared and variations between them is determined as 2.5 cm.

Precise Point Positioning Model Using Triple GNSS Constellations: GPS, Galileo and BeiDou

2016 ◽  
Vol 10 (4) ◽  
Author(s):  
Akram Afifi ◽  
Ahmed El-Rabbany
Keyword(s):  
Real Time ◽  
Urban Areas ◽  
Precise Point Positioning ◽  
Convergence Time ◽  
Dual Frequency ◽  
Post Processing ◽  
International Gnss Service ◽  
Time Service ◽  
System Bias ◽  
Point Positioning

AbstractThis paper introduces a comparison between dual-frequency precise point positioning (PPP) post-processing model, which combines the observations of three different GNSS constellations, namely GPS, Galileo, and BeiDou and real-time PPP model. A drawback of a single GNSS system such as GPS, however, is the availability of sufficient number of visible satellites in urban areas. Combining GNSS observations offers more visible satellites to users, which in turn is expected to enhance the satellite geometry and the overall positioning solution. However, combining several GNSS observables introduces additional biases, which require rigorous modelling, including the GNSS time offsets and hardware delays. In this paper, a GNSS post-processing PPPP model is developed using ionosphere-free linear combination. The additional biases of the GPS, Galileo, and BeiDou combination are accounted for through the introduction of a new unknown parameter, which is identified as the inter-system bias, in the PPP mathematical model. Natural Resources Canada’s GPSPace PPP software is modified to enable a combined GPS / Galileo / BeiDou PPP solution and to handle the newly inter-system bias. A total of four data sets at four IGS stations are processed to verify the developed PPP model. Precise satellite orbit and clock products from the IGS-MGEX network are used to correct of the GPS, Galileo and BeiDou measurements. For the real-time PPP model the corrections of the satellites orbit and clock are obtained through the international GNSS service (IGS) real-time service (RTS). GPS and Galileo Observations are used for the GNSS RTS-IGS PPP model as the RTS-IGS satellite products are not available for BeiDou satellites. This paper provides the GNSS RTS-IGS PPP model using different satellite clock corrections namely: IGS01, IGC01, IGS01, and IGS03. All PPP models results of convergence time and positioning precision are compared to the traditional GPS-only PPP model. It is shown that combining GPS, Galileo, and BeiDou observations in a PPP model reduces the convergence time by 25 % compared with the GPS-only PPP model.

scholarly journals Posicionamento GNSS em Tempo Real: Evolução, Aplicações Práticas e Perspectivas para o Futuro

2020 ◽  
Vol 72 ◽  
pp. 1359-1379
Author(s):  
Claudia Pereira Krueger ◽  
Paulo Sérgio de Oliveira Junior ◽  
Silvio Jacks dos Anjos Garnés ◽  
Daniele Barroca Marra Alves ◽  
Jorge Felipe Euriques
Keyword(s):  
Real Time ◽  
Global Positioning System ◽  
Precise Point Positioning ◽  
Reference Station ◽  
Space Representation ◽  
Positioning System ◽  
Differential Gps ◽  
Virtual Reference ◽  
State Space Representation ◽  
Global Positioning

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.

scholarly journals Development of the Kinematic Global Positioning System Precise Point Positioning Method Using 3-Pass Filter

2012 ◽  
Vol 29 (3) ◽  
pp. 269-274 ◽  
Author(s):  
Byung-Kyu Choi ◽  
Kyoung-Min Roh ◽  
Sung-Ki Cho ◽  
Jong-Uk Park ◽  
Pil-Ho Park ◽  
...  
Keyword(s):  
Global Positioning System ◽  
Precise Point Positioning ◽  
Positioning System ◽  
Pass Filter ◽  
Global Positioning ◽  
Positioning Method ◽  
Point Positioning

scholarly journals Precise Point Positioning Using Triple GNSS Constellations in Various Modes

2021 ◽  
Author(s):  
Akram Afifi ◽  
Ahmed El-Rabbany
Keyword(s):  
Linear Combination ◽  
Real Time ◽  
Precise Point Positioning ◽  
Satellite Orbit ◽  
Convergence Time ◽  
Dual Frequency ◽  
Post Processing ◽  
Time Service ◽  
Reference Satellite ◽  
Point Positioning

This paper introduces a new dual-frequency precise point positioning (PPP) model, which combines the observations from three different global navigation satellite system (GNSS) constellations, namely GPS, Galileo, and BeiDou. Combining measurements from different GNSS systems introduces additional biases, including inter-system bias and hardware delays, which require rigorous modelling. Our model is based on the un-differenced and between-satellite single-difference (BSSD) linear combinations. BSSD linear combination cancels out some receiver-related biases, including receiver clock error and non-zero initial phase bias of the receiver oscillator. Forming the BSSD linear combination requires a reference satellite, which can be selected from any of the GPS, Galileo, and BeiDou systems. In this paper three BSSD scenarios are tested; each considers a reference satellite from a different GNSS constellation. Natural Resources Canada’s GPSPace PPP software is modified to enable a combined GPS, Galileo, and BeiDou PPP solution and to handle the newly introduced biases. A total of four data sets collected at four different IGS stations are processed to verify the developed PPP model. Precise satellite orbit and clock products from the International GNSS Service Multi-GNSS Experiment (IGS-MGEX) network are used to correct the GPS, Galileo, and BeiDou measurements in the post-processing PPP mode. A real-time PPP solution is also obtained, which is referred to as RT-PPP in the sequel, through the use of the IGS real-time service (RTS) for satellite orbit and clock corrections. However, only GPS and Galileo observations are used for the RT-PPP solution, as the RTS-IGS satellite products are not presently available for BeiDou system. All post-processed and real-time PPP solutions are compared with the traditional un-differenced GPS-only counterparts. It is shown that combining the GPS, Galileo, and BeiDou observations in the post-processing mode improves the PPP convergence time by 25% compared with the GPS-only counterpart, regardless of the linear combination used. The use of BSSD linear combination improves the precision of the estimated positioning parameters by about 25% in comparison with the GPS-only PPP solution. Additionally, the solution convergence time is reduced to 10 minutes for the BSSD model, which represents about 50% reduction, in comparison with the GPS-only PPP solution. The GNSS RT-PPP solution, on the other hand, shows a similar convergence time and precision to the GPS-only counterpart.

Performance Evaluation of Kinematic BDS/GNSS Real-Time Precise Point Positioning for Maritime Positioning

2018 ◽  
Vol 72 (1) ◽  
pp. 34-52 ◽  
Author(s):  
Fuxin Yang ◽  
Lin Zhao ◽  
Liang Li ◽  
Shaojun Feng ◽  
Jianhua Cheng
Keyword(s):  
Real Time ◽  
Precise Point Positioning ◽  
Cost Effective ◽  
Satellite System ◽  
Convergence Time ◽  
Kinematic Data ◽  
Position Accuracy ◽  
Global Positioning ◽  
Cost Effective Technique ◽  
Point Positioning

Real-time Precise Point Positioning (PPP) has been evolved as a cost-effective technique for highly precise maritime positioning. For a long period, maritime PPP technology has mainly relied on the Global Positioning System (GPS). With the revitalisation of GLONASS and the emerging BeiDou navigation satellite system (BDS), it is now feasible to investigate real-time navigation performance of multi-constellation maritime PPP with GPS, BDS and GLONASS. In this contribution, we focus on maritime PPP performance using real world maritime kinematic data and real-time satellite correction products. The results show that BDS has lower position accuracy and slower convergence time than GPS. The BDS and GPS combination has the best performance among the dual-constellation configurations. Meanwhile, the integration of BDS, GLONASS and GPS significantly improves the position accuracy and the convergence time. Some outliers in the single constellation configuration can be mitigated when multi-constellation observations are utilised.

scholarly journals Precise Point Positioning Using Triple GNSS Constellations in Various Modes

2021 ◽  
Author(s):  
Akram Afifi ◽  
Ahmed El-Rabbany
Keyword(s):  
Linear Combination ◽  
Real Time ◽  
Precise Point Positioning ◽  
Satellite Orbit ◽  
Convergence Time ◽  
Dual Frequency ◽  
Post Processing ◽  
Time Service ◽  
Reference Satellite ◽  
Point Positioning

This paper introduces a new dual-frequency precise point positioning (PPP) model, which combines the observations from three different global navigation satellite system (GNSS) constellations, namely GPS, Galileo, and BeiDou. Combining measurements from different GNSS systems introduces additional biases, including inter-system bias and hardware delays, which require rigorous modelling. Our model is based on the un-differenced and between-satellite single-difference (BSSD) linear combinations. BSSD linear combination cancels out some receiver-related biases, including receiver clock error and non-zero initial phase bias of the receiver oscillator. Forming the BSSD linear combination requires a reference satellite, which can be selected from any of the GPS, Galileo, and BeiDou systems. In this paper three BSSD scenarios are tested; each considers a reference satellite from a different GNSS constellation. Natural Resources Canada’s GPSPace PPP software is modified to enable a combined GPS, Galileo, and BeiDou PPP solution and to handle the newly introduced biases. A total of four data sets collected at four different IGS stations are processed to verify the developed PPP model. Precise satellite orbit and clock products from the International GNSS Service Multi-GNSS Experiment (IGS-MGEX) network are used to correct the GPS, Galileo, and BeiDou measurements in the post-processing PPP mode. A real-time PPP solution is also obtained, which is referred to as RT-PPP in the sequel, through the use of the IGS real-time service (RTS) for satellite orbit and clock corrections. However, only GPS and Galileo observations are used for the RT-PPP solution, as the RTS-IGS satellite products are not presently available for BeiDou system. All post-processed and real-time PPP solutions are compared with the traditional un-differenced GPS-only counterparts. It is shown that combining the GPS, Galileo, and BeiDou observations in the post-processing mode improves the PPP convergence time by 25% compared with the GPS-only counterpart, regardless of the linear combination used. The use of BSSD linear combination improves the precision of the estimated positioning parameters by about 25% in comparison with the GPS-only PPP solution. Additionally, the solution convergence time is reduced to 10 minutes for the BSSD model, which represents about 50% reduction, in comparison with the GPS-only PPP solution. The GNSS RT-PPP solution, on the other hand, shows a similar convergence time and precision to the GPS-only counterpart.

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