scholarly journals Observing geometry effects on a Global Navigation Satellite System (GNSS)-based water vapor tomography solved by least squares and by compressive sensing

2020 ◽  
Vol 38 (1) ◽  
pp. 179-189
Author(s):  
Marion Heublein ◽  
Patrick Erik Bradley ◽  
Stefan Hinz
Keyword(s):  
Water Vapor ◽  
Compressive Sensing ◽  
Least Squares ◽  
Global Navigation Satellite System ◽  
Tomographic Reconstruction ◽  
Wrf Model ◽  
Satellite System ◽  
Navigation Satellite ◽  
Global Navigation ◽  
Global Navigation Satellite

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.

scholarly journals Observing geometry effects on a GNSS based water vapor tomography solved by Least Squares and by Compressive Sensing

2019 ◽  
Author(s):  
Marion Heublein ◽  
Patrick Erik Bradley ◽  
Stefan Hinz
Keyword(s):  
Water Vapor ◽  
Compressive Sensing ◽  
Least Squares ◽  
Tomographic Reconstruction ◽  
Wrf Model ◽  
Satellite System ◽  
Weather Research And Forecasting ◽  
Data Sets ◽  
Reconstruction Quality ◽  
Global Navigation Satellite

Abstract. In this work, the effect of the observing geometry on the tomographic reconstruction quality of both a regularized Least Squares (LSQ) and a Compressive Sensing (CS) approach for neutrospheric 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 resp. 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 inter site 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.

scholarly journals Validation of the Water Vapor Profiles of the Raman Lidar at the Maïdo Observatory (Reunion Island) Calibrated with Global Navigation Satellite System Integrated Water Vapor

Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 713 ◽  
Author(s):  
Hélène Vérèmes ◽  
Guillaume Payen ◽  
Philippe Keckhut ◽  
Valentin Duflot ◽  
Jean-Luc Baray ◽  
...  
Keyword(s):  
Water Vapor ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Navigation Satellite ◽  
Reunion Island ◽  
Raman Lidar ◽  
Réunion Island ◽  
Global Navigation ◽  
Global Navigation Satellite ◽  
Good Agreement

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.

A Signal Quality Monitoring Based on Least-Squares for Global Navigation Satellite System

2011 ◽  
Vol 383-390 ◽  
pp. 7582-7587
Author(s):  
Hai Long Chen ◽  
Yan Bo Zhu ◽  
Rui Xue
Keyword(s):  
Least Squares ◽  
Global Navigation Satellite System ◽  
Least Squares Method ◽  
Satellite System ◽  
Quality Monitoring ◽  
Quadratic Model ◽  
Signal Quality ◽  
Navigation Satellite ◽  
Global Navigation ◽  
Global Navigation Satellite

Signal Quality Monitoring (SQM) proposes to detect anomalous Global Navigation Satellite System (GNSS) signal distortions primarily through the using the multi-correlator receivers. These receivers employ three or more correlator pairs per channel-each slaved to tracking pairs. Then the measurements from each channel are transformed to form detection metrics. However, previously such some metrics were only simple algebraic combinations of the measurements and did not describe truly the characteristics of the correlation peak. This paper introduced a metric which uses measurements of each channel to fit the quadratic model with least-squares method to monitor the GNSS signal.

scholarly journals Multi-year Precipitable Water Vapor Observations in East Manila, Philippines using Radiosonde and Global Navigation Satellite System

2020 ◽  
Vol 199 ◽  
pp. 00002
Author(s):  
Agana Louisse S. Domingo ◽  
Ernest P. Macalalad
Keyword(s):  
Water Vapor ◽  
Surface Temperature ◽  
Global Navigation Satellite System ◽  
Precipitable Water ◽  
Satellite System ◽  
Precipitable Water Vapor ◽  
Type I ◽  
Navigation Satellite ◽  
Global Navigation ◽  
Global Navigation Satellite

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.

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
Keyword(s):  
Water Vapor ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Parameter Estimates ◽  
Navigation Satellite ◽  
Observation Model ◽  
Dual Frequency ◽  
Gps Satellites ◽  
Global Navigation ◽  
Global Navigation Satellite

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.

scholarly journals REVIEW OF TOMOGRAPHIC RECONSTRUCTION METHODS OF THE IONOSPHERE USING GNSS

2015 ◽  
Vol 33 (3) ◽  
pp. 445
Author(s):  
Fabricio Dos Santos Prol ◽  
Paulo De Oliveira Camargo
Keyword(s):  
Electron Density ◽  
Global Navigation Satellite System ◽  
Tomographic Reconstruction ◽  
Satellite System ◽  
Spatial And Temporal Variation ◽  
Navigation Satellite ◽  
Global Navigation ◽  
Ionospheric Imaging ◽  
Global Navigation Satellite ◽  
Grid Based

ABSTRACT. Spatial and temporal variation of the electron density in the atmosphere makes the ionosphere a difficult region to model. A major difficulty arises due to the incomplete geometrical coverage of the Global Navigation Satellite System (GNSS) for tomographic applications, making the ionospheric tomographic system an ill-conditioned problem. Although the tomographic system is ill-conditioned, several techniques have been developed to partially overcome the problem. There is great interest in using tomographic techniques for ionospheric imaging, because it allows describing the ionosphere in terms of electron density, which is an important parameter for studying the behavior of the physical processes that occur in the upper atmosphere. In Brazil, there are additional interests in the tomographic techniques, due to the peculiar characteristics of the ionosphere and of the geomagnetic field over the region. In this direction, methods of ionospheric tomographic reconstruction are presented and discussed in this review. Particular emphasis is given to the mathematical formulation from grid-based and function-based methods and are presented some of their main advantages and limitations.Keywords: TEC, Inverse Problem, Grid-Based Tomography, Function-Based Tomography, Ionospheric Imaging. RESUMO. A variação espaço-temporal da densidade eletrônica na atmosfera terrestre torna a ionosfera uma região de difícil modelagem. A principal dificuldade no imageamento da ionosfera com o GNSS (Global Navigation Satellite System ) é devido à geometria dos satélites, pois torna o sistema tomográfico mal condicionado. Muito embora a geometria não permita solução direta do sistema, diversas técnicas foram desenvolvidas para parcialmente superar tal problema. Há grande interesse no uso de técnicas de tomografia para o imageamento da ionosfera, pois permitem descrever a ionosfera ao nível da densidade eletrônica, sendo este um importante parâmetro para compreender os processos físicos que ocorrem na alta atmosfera. No Brasil, existem interesses adicionais no imageamento ionosférico por meio de técnicas tomográficas devido às características peculiares da ionosfera e do campo geomagnético sobre a região. Neste sentido, métodos utilizados para a reconstrução tomográfica da ionosfera são apresentados e discutidos nesta revisão. Uma ênfase especial é dada para a formulação matemática dos métodos baseados em células e em funções, além da apresentação de algumas de suas principais vantagens e limitações.Palavras-chave: TEC, Problema Inverso, Tomografia Baseada em Células, Tomografia Baseada em Funções, Imageamento Ionosférico.

scholarly journals So sánh lượng hơi nước tích tụ tính bằng GNSS và bằng bóng thám không tại trạm Tân Sơn Hòa, thành phố Hồ Chí Minh

2014 ◽  
pp. 21-28
Author(s):  
Nguyễn Định Quốc Huỳnh ◽  
Ngọc Lâu Nguyễn
Keyword(s):  
Water Vapor ◽  
Global Navigation Satellite System ◽  
Precipitable Water ◽  
Satellite System ◽  
Precipitable Water Vapor ◽  
Navigation Satellite ◽  
Global Navigation ◽  
Global Navigation Satellite

Lượng hơi nước tích tụ PWV (Precipitable Water Vapor) trong khí quyển rất cần thiết trong công tác dự báo thời tiết. Việc xác định chỉ số PWV một cách chính xác hiện nay đang là vấn đề được nhiều người quan tâm trong lĩnh vực khí tượng thủy văn. Trong bài báo này, chúng tôi trình bày thuật toán xác định chỉ số PWV và kết quả so sánh giá trị PWV từ dữ liệu bóng thám không và từ dữ liệu GNSS (Global Navigation Satellite System) tại trạm Tân Sơn Hòa TP.HCM. Độ lệch giữa các kết quả PWV nhỏ hơn 1.2mm. Ngoài ra giá trị PWV thay đổi phù hợp với thời tiết thay đổi trong ngày khảo sát.

scholarly journals OutFin, a multi-device and multi-modal dataset for outdoor localization based on the fingerprinting approach

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Fahad Alhomayani ◽  
Mohammad H. Mahoor
Keyword(s):  
Global Navigation Satellite System ◽  
Urban Areas ◽  
Satellite System ◽  
Reference Points ◽  
Navigation Satellite ◽  
Data Types ◽  
Entry Barrier ◽  
Promising Alternative ◽  
Global Navigation ◽  
Global Navigation Satellite

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.

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