scholarly journals Performance Evaluation of Troposphere Estimated from Galileo-Only Multi-Frequency Observations

2020 ◽  
Vol 12 (3) ◽  
pp. 373 ◽  
Author(s):  
Lewen Zhao ◽  
Pavel Václavovic ◽  
Jan Douša

The tropospheric delays estimated from the Global Navigation Satellite System (GNSS) have been proven to be an efficient product for monitoring variations of water vapor, which plays an important role in meteorology applications. The operational GNSS water vapor monitoring system is currently based on the Global Positioning System (GPS) and GLObal NAvigation Satellite System(GLONASS) dual-frequency observations. The Galileo satellite navigation system has been evolving continuously, and on 11 February 2019, the constellation reached 22 active satellites, achieving a capability of standalone Precise Point Positioning (PPP) and tropospheric estimation that is global in scope. This enhancement shows a 37% improvement if the precision of the Galileo-only zenith tropospheric delay, while we may anticipate further benefits in terms of tropospheric gradients and slant delays in the future if an optimal multi-constellation and multi-frequency processing strategy is used. First, we analyze the performance of the multi-frequency troposphere estimates based on the PPP raw observation model by comparing it with the standard ionosphere-free model. The performance of the Galileo-only tropospheric solution is then validated with respect to GPS-only solution using 48 globally distributed Multi-GNSS Experiment (MGEX) stations. The averaged bias and standard deviations are −0.3 and 5.8 mm when only using GPS satellites, respectively, and 0.0 and 6.2 mm for Galileo, respectively, when compared to the International GNSS Service (IGS) final Zenith Troposphere Delay(ZTD) products. Using receiver antenna phase center corrections from the corresponding GPS dual-frequency observations does not affect the Galileo PPP ambiguity float troposphere solutions. These results demonstrate a comparable precision achieved for both Galileo-only and GPS-only ZTD solutions, however, horizontal tropospheric gradients, estimated from standalone GPS and Galileo solutions, still show larger discrepancies, mainly due to their being less Galileo satellites than GPS satellites. Including Galileo E1, E5a, E5b, and E5 signals, along with their proper observation weighting, show the benefit of multi-frequency observations, further improving the ZTD precision by 4% when compared to the dual-frequency raw observation model. Overall, the presented results demonstrate good prospects for the application of multi-frequency Galileo observations for the tropospheric parameter estimates.

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.


Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 713 ◽  
Author(s):  
Hélène Vérèmes ◽  
Guillaume Payen ◽  
Philippe Keckhut ◽  
Valentin Duflot ◽  
Jean-Luc Baray ◽  
...  

The Maïdo high-altitude observatory located in Reunion Island (21 ∘ S, 55.5 ∘ E) is equipped with the Lidar1200, an innovative Raman lidar designed to measure the water vapor mixing ratio in the troposphere and the lower stratosphere, to perform long-term survey and processes studies in the vicinity of the tropopause. The calibration methodology is based on a GNSS (Global Navigation Satellite System) IWV (Integrated Water Vapor) dataset. The lidar water vapor measurements from November 2013 to October 2015 have been calibrated according to this methodology and used to evaluate the performance of the lidar. The 2-year operation shows that the calibration uncertainty using the GNSS technique is in good agreement with the calibration derived using radiosondes. During the MORGANE (Maïdo ObservatoRy Gaz and Aerosols NDACC Experiment) campaign (Reunion Island, May 2015), CFH (Cryogenic Frost point Hygrometer) radiosonde and Raman lidar profiles are compared and show good agreement up to 22 km asl; no significant biases are detected and mean differences are smaller than 9% up to 22 km asl.


2020 ◽  
Vol 199 ◽  
pp. 00002
Author(s):  
Agana Louisse S. Domingo ◽  
Ernest P. Macalalad

Precipitable water vapor (PWV) is a parameter that used to describe the water vapor content in the atmosphere has the potential to become a precipitation. Thus, it is important to measure PWV and investigate its trends and variability for potential forecasting precipitation. This study presents the variation of PWV at Tanay Upper Station (14°34’52.8”N, 121°22’08.9”E) from radiosonde operated by the Philippine Atmospheric, Geophysical and Astronomical Services Administration and at PIMO station (14°38’08.5”N, 121°04’39.4”E) using Global Navigation Satellite System (GNSS) operated by NASAJet Propulsion Laboratory under the International GNSS Service (IGS) network from 2015-2017. Moreover, there is no significant difference (p-values < 0.05) among PWV radiosonde, GNSS-PWV and rainfall as a function of year of observation. Monthly mean variation conforms to the Coronas climate classification, Climate Type I, in terms of the amount of precipitation. It is shown that PWV is high during wet months and least during dry months (November to April). Further, monthly mean variation is moderate correlated with surface temperature from radiosonde (R = +0.589). Evaporation rate depends on the surface temperature, which contributes in forming water vapor. The results showed that PWV from radiosonde gave reasonable values to be considered during wet and dry season as well as the seasonal variation of rainfall.


2021 ◽  
Author(s):  
Mohammad Al-Khaldi ◽  
Joel Johnson ◽  
Scott Gleason

&lt;p&gt;NASA's Cyclone Global Navigation Satellite System (CYGNSS) mission has continued to provide measurements of land surface specular scattering since its launch in December 2016. CYGNSS&amp;#8217;s operates in a GNSS-R configuration in which &amp;#160;CYGNSS satellites together with GPS satellites form a bistatic radar geometry with GPS satellites acting as transmitters and CYGNSS satellites acting as receivers. The fundamental GNSS-R measurement obtained using the CYGNSS observatories is the delay-Doppler map (DDM), from which normalized radar cross section (NRCS) estimates are derived. The sensitivity of CYGNSS measurements to a wide range of surface properties has motivated their use for soil moisture retrievals.&lt;/p&gt;&lt;p&gt;This presentation reports an updated analysis of soil moisture retrieval errors using a previously reported time series soil moisture retrieval algorithm that considers a &amp;#160;multi-year CYGNSS dataset. The presentation also reports recent progress in which further simplifications to the proposed algorithm are introduced that limit its need for ancillary soil moisture data and promote use in an operational capacity. This is accomplished, in part, through the incorporation of a recently developed global Level-1 coherence detection methodology and the use of a soil moisture climatology.&lt;/p&gt;&lt;p&gt;Soil moisture is sensed using a time-series retrieval in which NRCS ratios derived from CYGNSS measurements are used to form a system of equations that can be solved for a times series of surface reflectivities. While the NRCS exhibits a dependence on a wide range of properties such as soil moisture, soil composition, vegetation cover, and surface roughness, NRCS ratios in consecutive acquisitions, at sufficiently low latency, exhibit a direct proportionality to reflectivity ratios that are a function of soil permittivity and therefore soil moisture. The dependence of NRCS ratios on reflectivity facilitates a location dependent inversion of reflectivity to soil moisture through a dielectric mixing model. The use of NRCS ratios however results in N-1 equations for the N soil moistures in the time series, thereby necessitating the incorporation of additional information typically expressed in terms of maximum and/or minimum soil moisture (or reflectivity) values over the time series when solving the system. These values can be obtained either from ancillary data from other systems or from a soil moisture climatology as incorporated in this presentation.&lt;/p&gt;&lt;p&gt;Retrieved moisture values from the updated algorithm are compared against observed values reported by the Soil Moisture Active Passive (SMAP) mission. The findings suggest that there exists potential for using GNSS-R systems for global soil moisture retrievals with an RMS error on the order of 0.06 cm&lt;sup&gt;3&lt;/sup&gt;/cm&lt;sup&gt;3&lt;/sup&gt; over varied terrain. The dependence of the algorithm&amp;#8217;s retrieval error on land cover class, soil texture, and moisture variability trends will be reported in detail in this presentation.&lt;/p&gt;


2019 ◽  
Vol 72 (5) ◽  
pp. 1331-1344
Author(s):  
Ahao Wang ◽  
Junping Chen ◽  
Yize Zhang ◽  
Jiexian Wang ◽  
Bin Wang

The new Global Positioning System (GPS) Civil Navigation Message (CNAV) has been transmitted by Block IIR-M and Block IIF satellites since April 2014, both on the L2C and L5 signals. Compared to the Legacy Navigation Message (LNAV), the CNAV message provides six additional parameters (two orbit parameters and four Inter-Signal Correction (ISC) parameters) for prospective civil users. Using the precise products of the International Global Navigation Satellite System Service (IGS), we evaluate the precision of satellite orbit, clock and ISCs of the CNAV. Additionally, the contribution of the six new parameters to GPS Single Point Positioning (SPP) is analysed using data from 22 selected Multi-Global Navigation Satellite System Experiment (MGEX) stations from a 30-day period. The results indicate that the CNAV/LNAV Signal-In-Space Range Error (SISRE) and orbit-only SISRE from January 2016 to March 2018 is of 0·5 m and 0·3 m respectively, which is improved in comparison with the results from an earlier period. The ISC precision of L1 Coarse/Acquisition (C/A) is better than 0·1 ns, and those of L2C and L5Q5 are about 0·4 ns. Remarkably, ISC correction has little effect on the single-frequency SPP for GPS users using civil signals (for example, L1C, L2C), whereas dual-frequency SPP with the consideration of ISCs results have an accuracy improvement of 18·6%, which is comparable with positioning accuracy based on an ionosphere-free combination of the L1P (Y) and L2P (Y) signals.


2020 ◽  
Vol 38 (1) ◽  
pp. 179-189
Author(s):  
Marion Heublein ◽  
Patrick Erik Bradley ◽  
Stefan Hinz

Abstract. In this work, the effect of the observing geometry on the tomographic reconstruction quality of both a regularized least squares (LSQ) approach and a compressive sensing (CS) approach for water vapor tomography is compared based on synthetic Global Navigation Satellite System (GNSS) slant wet delay (SWD) estimates. In this context, the term “observing geometry” mainly refers to the number of GNSS sites situated within a specific study area subdivided into a certain number of volumetric pixels (voxels) and to the number of signal directions available at each GNSS site. The novelties of this research are (1) the comparison of the observing geometry's effects on the tomographic reconstruction accuracy when using LSQ or CS for the solution of the tomographic system and (2) the investigation of the effect of the signal directions' variability on the tomographic reconstruction. The tomographic reconstruction is performed based on synthetic SWD data sets generated, for many samples of various observing geometry settings, based on wet refractivity information from the Weather Research and Forecasting (WRF) model. The validation of the achieved results focuses on a comparison of the refractivity estimates with the input WRF refractivities. The results show that the recommendation of Champollion et al. (2004) to discretize the analyzed study area into voxels with horizontal sizes comparable to the mean GNSS intersite distance represents a good rule of thumb for both LSQ- and CS-based tomography solutions. In addition, this research shows that CS needs a variety of at least 15 signal directions per site in order to estimate the refractivity field more accurately and more precisely than LSQ. Therefore, the use of CS is particularly recommended for water vapor tomography applications for which a high number of multi-GNSS SWD estimates are available.


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.


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