Generation of Satellite Clock Offset for Global Navigation Satellite System Simulation

Author(s):  
Sha Hai ◽  
Yang Wen-ke ◽  
Li Peng-peng ◽  
Zhang Guo-zhu ◽  
Ou Gang
2020 ◽  
Vol 12 (11) ◽  
pp. 1821
Author(s):  
Qingsong Ai ◽  
Yunbin Yuan ◽  
Baocheng Zhang ◽  
Tianhe Xu ◽  
Yongchang Chen

Because of the frequency division multiple access (FDMA) technique, Russian global navigation satellite system (GLONASS) observations suffer from pseudo-range inter-channel biases (ICBs), which adversely affect satellite clock offset estimation. In this study, the GLONASS pseudo-range ICB is treated in four different ways: as ignorable parameters (ICB-NONE), polynomial functions of frequency (ICB-FPOL), frequency-specific parameters (ICB-RF), and satellite-specific parameters (ICB-RS). Data from 110 international global navigation satellite system (GNSS) service stations were chosen to obtain the ICBs and were used for satellite clock offset estimation. The ICBs from the different schemes varied from −20 ns to 80 ns. The ICB-RS model yielded the best results, improving the clock offset accuracy from 300 ps to about 100 ps; it could improve the GLONASS precise point positioning (PPP) accuracy and the converging time by approximately 50% and 30%, respectively. Along similar lines, we introduced the GPS-ICB parameters in the process of GPS satellite clock estimation and GPS/GLONASS PPP, as ICBs may exist for GPS because of different chip shape distortions among GPS satellites. This possibility was found to be the case. Further, the GPS-ICB magnitude ranged from −2 ns to 2 ns, and the estimated satellite clock offsets could improve the accuracy of the GPS and combined GPS/GLONASS PPP by 10%; it also accelerated the converging time by more than 15% thanks to the GPS-ICB calibration.


2019 ◽  
Vol 11 (8) ◽  
pp. 992
Author(s):  
Li ◽  
Xu ◽  
Flechtner ◽  
Förste ◽  
Lu ◽  
...  

Conventional relative kinematic positioning is difficult to be applied in the polar region of Earth since there is a very sparse distribution of reference stations, while precise point positioning (PPP), using data of a stand-alone receiver, is recognized as a promising tool for obtaining reliable and accurate trajectories of moving platforms. However, PPP and its integer ambiguity fixing performance could be much degraded by satellite orbits and clocks of poor quality, such as those of the geostationary Earth orbit (GEO) satellites of the BeiDou navigation satellite system (BDS), because temporal variation of orbit errors cannot be fully absorbed by ambiguities. To overcome such problems, a network-based processing, referred to as precise orbit positioning (POP), in which the satellite clock offsets are estimated with fixed precise orbits, is implemented in this study. The POP approach is validated in comparison with PPP in terms of integer ambiguity fixing and trajectory accuracy. In a simulation test, multi-GNSS (global navigation satellite system) observations over 14 days from 136 globally distributed MGEX (the multi-GNSS Experiment) receivers are used and four of them on the coast of Antarctica are processed in kinematic mode as moving stations. The results show that POP can improve the ambiguity fixing of all system combinations and significant improvement is found in the solution with BDS, since its large orbit errors are reduced in an integrated adjustment with satellite clock offsets. The four-system GPS+GLONASS+Galileo+BDS (GREC) fixed solution enables the highest 3D position accuracy of about 3.0 cm compared to 4.3 cm of the GPS-only solution. Through a real flight experiment over Antarctica, it is also confirmed that POP ambiguity fixing performs better and thus can considerably speed up (re-)convergence and reduce most of the fluctuations in PPP solutions, since the continuous tracking time is short compared to that in other regions.


2017 ◽  
Vol 145 (2) ◽  
pp. 637-651 ◽  
Author(s):  
S. Mark Leidner ◽  
Thomas Nehrkorn ◽  
John Henderson ◽  
Marikate Mountain ◽  
Tom Yunck ◽  
...  

Global Navigation Satellite System (GNSS) radio occultations (RO) over the last 10 years have proved to be a valuable and essentially unbiased data source for operational global numerical weather prediction. However, the existing sampling coverage is too sparse in both space and time to support forecasting of severe mesoscale weather. In this study, the case study or quick observing system simulation experiment (QuickOSSE) framework is used to quantify the impact of vastly increased numbers of GNSS RO profiles on mesoscale weather analysis and forecasting. The current study focuses on a severe convective weather event that produced both a tornado and flash flooding in Oklahoma on 31 May 2013. The WRF Model is used to compute a realistic and faithful depiction of reality. This 2-km “nature run” (NR) serves as the “truth” in this study. The NR is sampled by two proposed constellations of GNSS RO receivers that would produce 250 thousand and 2.5 million profiles per day globally. These data are then assimilated using WRF and a 24-member, 18-km-resolution, physics-based ensemble Kalman filter. The data assimilation is cycled hourly and makes use of a nonlocal, excess phase observation operator for RO data. The assimilation of greatly increased numbers of RO profiles produces improved analyses, particularly of the lower-tropospheric moisture fields. The forecast results suggest positive impacts on convective initiation. Additional experiments should be conducted for different weather scenarios and with improved OSSE systems.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Fahad Alhomayani ◽  
Mohammad H. Mahoor

AbstractIn recent years, fingerprint-based positioning has gained researchers’ attention since it is a promising alternative to the Global Navigation Satellite System and cellular network-based localization in urban areas. Despite this, the lack of publicly available datasets that researchers can use to develop, evaluate, and compare fingerprint-based positioning solutions constitutes a high entry barrier for studies. As an effort to overcome this barrier and foster new research efforts, this paper presents OutFin, a novel dataset of outdoor location fingerprints that were collected using two different smartphones. OutFin is comprised of diverse data types such as WiFi, Bluetooth, and cellular signal strengths, in addition to measurements from various sensors including the magnetometer, accelerometer, gyroscope, barometer, and ambient light sensor. The collection area spanned four dispersed sites with a total of 122 reference points. Each site is different in terms of its visibility to the Global Navigation Satellite System and reference points’ number, arrangement, and spacing. Before OutFin was made available to the public, several experiments were conducted to validate its technical quality.


2010 ◽  
Vol 63 (2) ◽  
pp. 269-287 ◽  
Author(s):  
S. Abbasian Nik ◽  
M. G. Petovello

These days, Global Navigation Satellite System (GNSS) technology plays a critical role in positioning and navigation applications. Use of GNSS is becoming more of a need to the public. Therefore, much effort is needed to make the civilian part of the system more accurate, reliable and available, especially for the safety-of-life purposes. With the recent revitalization of Russian Global Navigation Satellite System (GLONASS), with a constellation of 20 satellites in August 2009 and the promise of 24 satellites by 2010, it is worthwhile concentrating on the GLONASS system as a method of GPS augmentation to achieve more reliable and accurate navigation solutions.


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