An Effect of Tropospheric Delay Irregularity among the Reference Stations on Precise Positioning

2016 ◽  
Author(s):  
Younghoon Han ◽  
Jaeyoung Ko ◽  
Mi Young Shin ◽  
Sang Hyun Park
Keyword(s):  
Tropospheric Delay ◽  
Precise Positioning

scholarly journals Tropospheric delay parameters from numerical weather models for multi-GNSS precise positioning

2016 ◽  
Vol 9 (12) ◽  
pp. 5965-5973 ◽  
Author(s):  
Cuixian Lu ◽  
Florian Zus ◽  
Maorong Ge ◽  
Robert Heinkelmann ◽  
Galina Dick ◽  
...  
Keyword(s):  
Processing System ◽  
Satellite System ◽  
Convergence Time ◽  
Tropospheric Delay ◽  
International Gnss Service ◽  
Positioning Accuracy ◽  
Precise Positioning ◽  
Numerical Weather ◽  
North East ◽  
The North

Abstract. The recent dramatic development of multi-GNSS (Global Navigation Satellite System) constellations brings great opportunities and potential for more enhanced precise positioning, navigation, timing, and other applications. Significant improvement on positioning accuracy, reliability, as well as convergence time with the multi-GNSS fusion can be observed in comparison with the single-system processing like GPS (Global Positioning System). In this study, we develop a numerical weather model (NWM)-constrained precise point positioning (PPP) processing system to improve the multi-GNSS precise positioning. Tropospheric delay parameters which are derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis are applied to the multi-GNSS PPP, a combination of four systems: GPS, GLONASS, Galileo, and BeiDou. Observations from stations of the IGS (International GNSS Service) Multi-GNSS Experiments (MGEX) network are processed, with both the standard multi-GNSS PPP and the developed NWM-constrained multi-GNSS PPP processing. The high quality and accuracy of the tropospheric delay parameters derived from ECMWF are demonstrated through comparison and validation with the IGS final tropospheric delay products. Compared to the standard PPP solution, the convergence time is shortened by 20.0, 32.0, and 25.0 % for the north, east, and vertical components, respectively, with the NWM-constrained PPP solution. The positioning accuracy also benefits from the NWM-constrained PPP solution, which was improved by 2.5, 12.1, and 18.7 % for the north, east, and vertical components, respectively.

scholarly journals Tropospheric delay parameters from numerical weather models for multi-GNSS precise positioning

2016 ◽  
Author(s):  
Cuixian Lu ◽  
Florian Zus ◽  
Maorong Ge ◽  
Robert Heinkelmann ◽  
Galina Dick ◽  
...  
Keyword(s):  
Processing System ◽  
Global Navigation Satellite Systems ◽  
Convergence Time ◽  
Tropospheric Delay ◽  
International Gnss Service ◽  
Positioning Accuracy ◽  
Precise Positioning ◽  
Numerical Weather ◽  
North East ◽  
The North

Abstract. The recent dramatic development of multi-GNSS (Global Navigation Satellite Systems) constellations brings great opportunities and potential for more enhanced precise positioning, navigation, timing, and other applications. Significant improvement on positioning accuracy, reliability, as well as convergence time with the multi-GNSS fusion can be observed in comparison with the single-system processing like GPS (Global Positioning System). In this study, we develop a numerical weather model (NWM)-constrained PPP processing system to improve the multi-GNSS precise positioning. Tropospheric delay parameters which are derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis are applied to the multi-GNSS PPP, a combination of four systems: GPS, GLONASS, Galileo, and BeiDou. Observations from stations of the IGS (International GNSS Service) Multi-GNSS Experiments (MGEX) network are processed, with both the standard multi-GNSS PPP and the developed NWM-constrained multi-GNSS PPP processing. The high quality and accuracy of the tropospheric delay parameters derived from ECMWF are demonstrated through comparison and validation with the IGS final tropospheric delay products. Compared to the standard PPP solution, the convergence time is shortened by 32.0 %, 37.5 %, and 25.0 % for the north, east, and vertical components, respectively, with the NWM-constrained PPP solution. The positioning accuracy also benefits from the NWM-constrained PPP solution, which gets improved by 2.5 %, 12.1 %, and 18.7 % for the north, east, and vertical components, respectively.

scholarly journals Robust Filtering Techniques for RTK Positioning in Harsh Propagation Environments

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1250
Author(s):  
Daniel Medina ◽  
Haoqing Li ◽  
Jordi Vilà-Valls ◽  
Pau Closas
Keyword(s):  
Intelligent Transportation Systems ◽  
Robust Statistics ◽  
Real Data ◽  
Transportation Systems ◽  
Global Navigation Satellite Systems ◽  
Mixed Integer ◽  
Robust Filtering ◽  
Precise Positioning ◽  
The Impact ◽  
Filtering Techniques

Global navigation satellite systems (GNSSs) play a key role in intelligent transportation systems such as autonomous driving or unmanned systems navigation. In such applications, it is fundamental to ensure a reliable precise positioning solution able to operate in harsh propagation conditions such as urban environments and under multipath and other disturbances. Exploiting carrier phase observations allows for precise positioning solutions at the complexity cost of resolving integer phase ambiguities, a procedure that is particularly affected by non-nominal conditions. This limits the applicability of conventional filtering techniques in challenging scenarios, and new robust solutions must be accounted for. This contribution deals with real-time kinematic (RTK) positioning and the design of robust filtering solutions for the associated mixed integer- and real-valued estimation problem. Families of Kalman filter (KF) approaches based on robust statistics and variational inference are explored, such as the generalized M-based KF or the variational-based KF, aiming to mitigate the impact of outliers or non-nominal measurement behaviors. The performance assessment under harsh propagation conditions is realized using a simulated scenario and real data from a measurement campaign. The proposed robust filtering solutions are shown to offer excellent resilience against outlying observations, with the variational-based KF showcasing the overall best performance in terms of Gaussian efficiency and robustness.

Precise positioning method for multi-process connecting based on binocular vision

2016 ◽  
Author(s):  
Wei Liu ◽  
Lichao Ding ◽  
Kai Zhao ◽  
Xiao Li ◽  
Ling Wang ◽  
...  
Keyword(s):  
Binocular Vision ◽  
Precise Positioning ◽  
Positioning Method

scholarly journals Precise positioning of mechanisms based on dynamics

2021 ◽  
Vol 1129 (1) ◽  
pp. 012064
Author(s):  
S Y Orekhov ◽  
V M Masyuk ◽  
V S Kuznetsov ◽  
S P Dolgolenko ◽  
K G Kislov
Keyword(s):  
Precise Positioning
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