Generating GPS decoupled clock products for precise point positioning with ambiguity resolution

2022 ◽  
Vol 96 (1) ◽  
Author(s):  
Shuai Liu ◽  
Yunbin Yuan
GPS Solutions ◽  
2020 ◽  
Vol 24 (3) ◽  
Author(s):  
Pan Li ◽  
Xinyuan Jiang ◽  
Xiaohong Zhang ◽  
Maorong Ge ◽  
Harald Schuh

2019 ◽  
Vol 71 (1) ◽  
Author(s):  
Georgia Katsigianni ◽  
Felix Perosanz ◽  
Sylvain Loyer ◽  
Mini Gupta

2020 ◽  
Vol 12 (11) ◽  
pp. 1853
Author(s):  
Jin Wang ◽  
Guanwen Huang ◽  
Qin Zhang ◽  
Yang Gao ◽  
Yuting Gao ◽  
...  

In this study, an uncombined precise point positioning (PPP) model was established and was used for estimating fractional cycle bias (FCB) products and for achieving ambiguity resolution (AR), using GPS, BDS-2, and Galileo raw observations. The uncombined PPP model is flexible and efficient for positioning services and generating FCB. The FCBs for GPS, BDS-2, and Galileo were estimated using the uncombined PPP model with observations from the Multi-GNSS Experiment (MGEX) stations. The root mean squares (RMSs) of the float ambiguity a posteriori residuals associated with all of the three GNSS constellations, i.e., GPS, BDS-2, and Galileo, are less than 0.1 cycles for both narrow-lane (NL) and wide-lane (WL) combinations. The standard deviation (STD) of the WL combination FCB series is 0.015, 0.013, and 0.006 cycles for GPS, BDS-2, and Galileo, respectively, and the counterpart for the NL combination FCB series is 0.030 and 0.0184 cycles for GPS and Galileo, respectively. For the BDS-2 NL combination FCB series, the STD of the inclined geosynchronous orbit (IGSO) satellites is 0.0156 cycles, while the value for the medium Earth orbit (MEO) satellites is 0.073 cycles. The AR solutions produced by the uncombined multi-GNSS PPP model were evaluated from the positioning biases and the success fixing rate of ambiguity. The experimental results demonstrate that the growth of the amount of available satellites significantly improves the PPP performance. The three-dimensional (3D) positioning accuracies associated with the PPP ambiguity-fixed solutions for the respective only-GPS, GPS/BDS-2, GPS/Galileo, and GPS/BDS-2/Galileo models are 1.34, 1.19, 1.21, and 1.14 cm, respectively, and more than a 30% improvement is achieved when compared to the results related to the ambiguity-float solutions. Additionally, the convergence time based on the GPS/BDS-2/Galileo observations is only 7.5 min for the ambiguity-fixed solutions, and the results exhibit a 53% improvement in comparison to the ambiguity-float solutions. The values of convergence time based on the only-GPS observations are estimated as 22 and 10.5 min for the ambiguity-float and ambiguity-fixed solutions, respectively. Lastly, the success fixing rate of ambiguity is also dramatically raised for the multi-GNSS PPP AR. For example, the percentage is approximately 99% for the GPS/BDS-2/Galileo solution over a 10 min processing period. In addition, the inter-system bias (ISB) between GPS, BDS-2, and Galileo, which is carefully considered in the uncombined multi-GNSS PPP method, is modeled as a white noise process. The differences of the ISB series between BDS-2 and Galileo indicate that the clock datum bias of the satellite clock offset estimation accounts for the variation of the ISB series.


GEOMATICA ◽  
2012 ◽  
Vol 66 (2) ◽  
pp. 103-111 ◽  
Author(s):  
S. Bisnath ◽  
P. Collins

In standard Precise Point Positioning (PPP), the carrier phase ambiguities are estimated as real-valued constants, so that the carrier-phases can provide similar information as the pseudoranges. As a consequence, it can take tens of minutes to several hours for the ambiguities to converge to suitably precise values. Recently, new processing methods have been identified that permit the ambiguities to be estimated more appropriately as integer-valued constants, as they are in relative Real-Time Kinematic (RTK) positioning. Under these conditions, standard ambiguity resolution techniques can be applied to strengthen the PPP solution. The result can be a greatly reduced solution convergence and re-convergence period, representing a significant step toward improving the performance of PPP with respect to that of RTK processing. This paper describes the underlying principles of the method, why the enhancements work, and presents some results.


Survey Review ◽  
2019 ◽  
Vol 52 (374) ◽  
pp. 442-453 ◽  
Author(s):  
V. Duong ◽  
K. Harima ◽  
S. Choy ◽  
D. Laurichesse ◽  
C. Rizos

2021 ◽  
Vol 13 (16) ◽  
pp. 3164
Author(s):  
Lizhong Qu ◽  
Pu Zhang ◽  
Changfeng Jing ◽  
Mingyi Du ◽  
Jian Wang ◽  
...  

We investigate the estimation of the fractional cycle biases (FCBs) for GPS triple-frequency uncombined precise point positioning (PPP) with ambiguity resolution (AR) based on the IGS ultra-rapid predicted (IGU) orbits. The impact of the IGU orbit errors on the performance of GPS triple-frequency PPP AR is also assessed. The extra-wide-lane (EWL), wide-lane (WL) and narrow-lane (NL) FCBs are generated with the single difference (SD) between satellites model using the global reference stations based on the IGU orbits. For comparison purposes, the EWL, WL and NL FCBs based on the IGS final precise (IGF) orbits are estimated. Each of the EWL, WL and NL FCBs based on IGF and IGU orbits are converted to the uncombined FCBs to implement the static and kinematic triple-frequency PPP AR. Due to the short wavelengths of NL ambiguities, the IGU orbit errors significantly impact the precision and stability of NL FCBs. An average STD of 0.033 cycles is achieved for the NL FCBs based on IGF orbits, while the value of the NL FCBs based on IGU orbits is 0.133 cycles. In contrast, the EWL and WL FCBs generated based on IGU orbits have comparable precision and stability to those generated based on IGF orbits. The use of IGU orbits results in an increased time-to-first-fix (TTFF) and lower fixing rates compared to the use of IGF orbits. Average TTFFs of 23.3 min (static) and 31.1 min (kinematic) and fixing rates of 98.1% (static) and 97.4% (kinematic) are achieved for the triple-frequency PPP AR based on IGF orbits. The average TTFFs increase to 27.0 min (static) and 37.9 min (kinematic) with fixing rates of 97.0% (static) and 96.3% (kinematic) based on the IGU orbits. The convergence times and positioning accuracy of PPP and PPP AR based on IGU orbits are slightly worse than those based on IGF orbits. Additionally, limited by the number of satellites transmitting three frequency signals, the introduction of the third frequency, L5, has a marginal impact on the performance of PPP and PPP AR. The GPS triple-frequency PPP AR performance is expected to improve with the deployment of new-generation satellites capable of transmitting the L5 signal.


Sign in / Sign up

Export Citation Format

Share Document