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Beidou/GNSS Precise Positioning and Atmospheric Modeling II

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 13651

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Prof. Dr. Yunbin Yuan

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Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
Interests: satellite geodesy; global navigation satellite system; precise orbit determination; positioning navigation and timing; tropospheric and ionospheric modeling
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Baocheng Zhang

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Guest Editor

Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430077, China
Interests: GNSS; precise point positioning; PPP-RTK
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The coexistence of multi-frequency and multi-constellation GNSS provides excellent opportunities for GNSS applications such as precise positioning, time transfer, and atmospheric modeling. The theory of multi-frequency and multi-constellation GNSS fusion data processing and the new results of classical GNSS applications in those scenarios have become the current research focus. Our last special issue (https://www.mdpi.com/journal/remotesensing/special_issues/Beidou_GNSS) attracted extensive attention in areas such as precise positioning, time transfer, atmospheric modeling, and precise orbit determination of LEO satellites. In this special issue, we continue to look forward to papers on the theories and applications of multi-frequency and multi-constellation GNSS. The range of applications considered is wide, but precise positioning, time transfer, atmospheric modeling, and precise orbit determination of LEO satellites will be the main area of focus. As a continuation of the previous special issue, we hope that this special issue will continue to contribute to the GNSS community.

Prof. Dr. Yunbin Yuan
Dr. Baocheng Zhang
Guest Editors

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Keywords

GNSS
PPP/RTK
ionosphere/troposphere
time and frequency transfer
LEO/navigational satellite orbit determination

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Related Special Issues

Beidou/GNSS Precise Positioning and Atmospheric Modeling II in Remote Sensing (8 articles)
Beidou/GNSS Precise Positioning and Atmospheric Modeling II in Remote Sensing (8 articles)

Published Papers (8 papers)

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Research

20 pages, 14313 KiB

Open AccessArticle

Optimized Integer Aperture Bootstrapping for High-Integrity CDGNSS Applications

by Jingbo Zhao, Ping Huang, Baoguo Yu, Lei Wang, Yao Wang, Chuanzhen Sheng, Qingwu Yi and Jianlei Yang

Remote Sens. 2024, 16(1), 118; https://doi.org/10.3390/rs16010118 - 27 Dec 2023

Viewed by 749

Abstract

Integer Aperture Bootstrapping (IAB) is a crucial method for testing ambiguity acceptance in carrier-phase differential global navigation satellite system (CDGNSS) positioning. It has the advantage that integrity parameters, such as the failure rate, can be analytically calculated, which is essential in safety-of-life applications. Although the IAB methods have been extensively studied, their threshold-determining method is still not well explained, theoretically. In this study, a new method, named Analytical Integer Aperture Bootstrapping (AIAB), is theoretically derived to determine the optimal IAB threshold. AIAB is novel in that: (1) a precise and easy-to-compute expression has been developed to describe the relationship between the IAB threshold and the failure rate, (2) an analytical function model has been derived from the expression to determine the IAB threshold; moreover, the function model is simplified, and (3) a data-constraint approach has been proposed to reduce the complexity of IAB. In the global CDGNSS simulations, AIAB is shown to outperform the existing IAB methods under both strong and weak models, particularly at low fix rates, which are 23% to 40% higher than the basic IAB method. The Monte Carlo simulation results show that AIAB can obtain almost theoretically the same performance as Optimal Integer Aperture (OIA). Full article

(This article belongs to the Special Issue Beidou/GNSS Precise Positioning and Atmospheric Modeling II)

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17 pages, 6333 KiB

Open AccessArticle

Advancing Precise Orbit Determination and Precise Point Positioning of BDS-3 Satellites from B1IB3I to B1CB2a: Comparison and Analysis

by Chen Wang, Tengjie Luo, Shitong Chen and Pan Li

Remote Sens. 2023, 15(20), 4926; https://doi.org/10.3390/rs15204926 - 12 Oct 2023

Cited by 1 | Viewed by 1075

Abstract

The third generation of the Chinese BeiDou Navigation Satellite System (BDS-3) broadcasts new signals, i.e., B1C, B2a, and B2b, along with the legacy signals of BDS-2 B1I and B3I. The novel signals are demonstrated to show adequate upgraded performance, due to the restrictions on the ground tracking network for the BDS-3 satellites in new frequency bands, and in order to maintain the consistency of the hybrid BDS-2 and BDS-3 orbit/clock products using the common B1IB3I data, the use of B1CB2a observations is not sufficient for both precise orbit determination (POD) and precise point positioning (PPP) applications. In this study, one-year data of 2022 from the International GNSS Service (IGS) and the International GNSS Monitoring and Assessment System (iGMAS) are used in the precise orbit and clock determination for BDS-3 satellites based on the two sets of observations (i.e., B1IB3I and B1CB2a), and the orbit and clock accuracy along with the PPP ambiguity resolution (AR) performance are investigated. In general, the validations demonstrate that clear improvement can be achieved for the B1CB2a-based solution for both POD and PPP. In comparison to the B1IB3I, using BDS-3 B1CB2a observations can help to improve orbit consistency by around 25% as indicated by orbit boundary discontinuities (OBDs), and this use can further reduce the bias and enhance the orbit accuracy as revealed by satellite laser ranging (SLR) residuals. Similar improvement was also identified in the satellite clock performance. The B1CB2a-based solution obtains decreased Allan deviation (ADEV) values in comparison with the B1IB3I-based solution by 6~12%. Regarding the PPP-AR performance, the advantage of B1CB2a observations is evidently reflected through the estimates of wide-lane/narrow-lane fractional cycle bias (FCB), convergence time, and positioning accuracy, in which a significant reduction over 10 min is found in the PPP convergence time. Full article

(This article belongs to the Special Issue Beidou/GNSS Precise Positioning and Atmospheric Modeling II)

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18 pages, 13262 KiB

Open AccessArticle

Investigating the ERA5-Based PWV Products and Identifying the Monsoon Active and Break Spells with Dense GNSS Sites in Guangxi, China

by Wen Liu, Lulu Zhang, Si Xiong, Liangke Huang, Shaofeng Xie and Lilong Liu

Remote Sens. 2023, 15(19), 4710; https://doi.org/10.3390/rs15194710 - 26 Sep 2023

Cited by 4 | Viewed by 1229

Abstract

Precipitable water vapor (PWV) with high precision and high temporal resolution estimated by Global Navigation Satellite System (GNSS) is widely used in atmospheric research and weather forecasting. However, most previous works are not consensual concerning the characteristics of the PWV at different time scales and the identification of active and break spells during summ er monsoon climate in Guangxi, China. Taking radiosonde (RS) observations as reference, a strong correlation (R > 0.97) exists between GNSS PWV and RS PWV with a mean root mean square error (RMSE) of 2.68 mm. The annual, seasonal, monthly, and diurnal PWV variations of three years (2017, 2018 and 2020) over Guangxi in were comprehensively investigated using 104 GNSS stations and the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis (ERA5). The mean annual bias and RMSE between GNSS PWV and ERA5 PWV are −1.04 mm and 2.63 mm, respectively. The monthly bias and RMSE range are −0.77 to 3.87 mm, 1.32 to 4.45 mm, and the daily range is −1.41 to 1.07 mm and 1.11 to 5.02 mm, respectively. Additionally, the adopted average standardized rainfall anomaly criteria also identified 7/7/3 active spells and 5/3/7 break spells during the summer monsoon (June–September) from 2017 to 2020, respectively. During the three-year period, the daily amplitude ranges for active spells varied from 1.41 to 2.49 mm, 0.69 to 5.4 mm, and 0.88 to 1.41 mm, while the ranges for break spells were 2.45 to 6.76 mm, 1.66 to 8.17 mm, and 1.48 to 2.99 mm, respectively. The results show a superior performance of GNSS PWV compared to ERA5 PWV in Guangxi, and the maximum, minimum and occurrence time of PWV anomaly vary slightly with the season and the topography of stations. Despite temperature primarily exhibiting a negative correlation with rainfall, acting as a dampener, a positive correlation remains evident between PWV and rainfall. Therefore, densely distributed GNSS stations exhibit excellent capabilities in quantifying atmospheric water vapor and facilitating real-time monitoring of small and medium-scale weather phenomena. Full article

(This article belongs to the Special Issue Beidou/GNSS Precise Positioning and Atmospheric Modeling II)

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19 pages, 6029 KiB

Open AccessArticle

A Novel Method for Monitoring Tropical Cyclones’ Movement Using GNSS Zenith Tropospheric Delay

by Dajun Lian, Qimin He, Li Li, Kefei Zhang, Erjiang Fu, Guangyan Li, Rui Wang, Biqing Gao and Kangming Song

Remote Sens. 2023, 15(13), 3247; https://doi.org/10.3390/rs15133247 - 23 Jun 2023

Cited by 2 | Viewed by 1497

Abstract

Precipitable water vapor (PWV) is an important meteorological factor for predicting extreme weather events such as tropical cyclones, which can be obtained from zenith tropospheric delay (ZTD) by using a conversion. A time difference of ZTD arrival (TDOZA) model was proposed to monitor the movement of tropical cyclones, and the fifth-generation reanalysis dataset of the European Centre for Medium-range Weather Forecasting (ERA5)-derived ZTD (ERA5-ZTD) was used to estimate the movement of tropical cyclones based on the model. The global navigation satellite system-derived ZTD and radiosonde data-derived PWV (RS-PWV) were used to test the accuracy of the ERA5-ZTD and analyze the correlation between ZTD and PWV, respectively. The statistics showed that the mean Bias, RMS and STD of the ERA5-ZTD were 6.4 mm, 17.1 mm and 16.5 mm, respectively, and the mean correlation coefficient of the ERA5-ZTD and RS-PWV was 0.951, which indicates that the ZTD can be used to predict weather events instead of PWV. Then, spatiao-temporal characteristics of ZTD during the four tropical cyclone (i.e., Merbok, ROKE, Neast and Hato) periods in 2017 were analyzed, and the result showed that the moving directions of ZTD and the tropical cyclones were consistent. Thus, the ZTD time series over the ERA5 grids around the tropical cyclones’ paths were used to estimate the velocity of the tropical cyclones based on the TDOZA model, when the tropical cyclones are approaching or leaving. Compared with the result from the China Meteorological Administration, the mean absolute and relative deviations of the TDOZA model-derived velocity were 2.55 km/h and 10.0%, respectively. These results suggest that ZTD can be used as a new supplementary meteorological parameter for monitoring tropical cyclone events. Full article

(This article belongs to the Special Issue Beidou/GNSS Precise Positioning and Atmospheric Modeling II)

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18 pages, 4380 KiB

Open AccessArticle

An Improved Parameter Estimation Method for High-Efficiency Multi-GNSS-Integrated Orbit Determination

by Xingyuan Yan, Chenchen Liu, Meng Yang, Wei Feng and Min Zhong

Remote Sens. 2023, 15(10), 2635; https://doi.org/10.3390/rs15102635 - 18 May 2023

Cited by 1 | Viewed by 1256

Abstract

The increased number of satellites and stations leads to the serious time consumption of the integrated precise orbit determination (POD), especially in the current global navigation satellite system (GNSS) with more than 120 satellites. To improve the computational efficiency of multi-GNSS-integrated POD, this paper proposed an improved parameter estimation method based on intel oneAPI high-performance computing, where the inactive parameters are eliminated in a batch mode. Compared with the classical estimation method based on the “one-by-one” elimination, the efficiencies were significantly improved with ratios of 2.53, 4.21, and 5.38 for 79, 126, and 171 stations’ GPS/BDS/Galileo/GLONASS-integrated POD, respectively. The elapsed time of the improved method by using 126 stations was the same as that of 79 stations’ POD by the classical estimation method. In terms of precision, the one-dimensional root mean square error (RMS) reductions were 0.1 cm (7%), 34.3 cm (11%), 1.9 cm (18%), 0.4 cm (8%), 0.2 cm (13%), and 0.4 cm (13%) for GPS, BDS GEO, BDS IGSO, BDS MEO, Galileo, and GLONASS satellites, respectively. Full article

(This article belongs to the Special Issue Beidou/GNSS Precise Positioning and Atmospheric Modeling II)

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18 pages, 4931 KiB

Open AccessArticle

Spatiotemporal Analysis of Regional Ionospheric TEC Prediction Using Multi-Factor NeuralProphet Model under Disturbed Conditions

by Ling Huang, Han Wu, Yidong Lou, Hongping Zhang, Lilong Liu and Liangke Huang

Remote Sens. 2023, 15(1), 195; https://doi.org/10.3390/rs15010195 - 30 Dec 2022

Cited by 5 | Viewed by 2059

Abstract

The ionospheric total electron content (TEC) is susceptible to factors, such as solar and geomagnetic activities, resulting in the enhancement of its non-stationarity and nonlinear characteristics, which aggravate the impact on radio communications. In this study, based on the NeuralProphet hybrid prediction framework, a regional ionospheric TEC prediction model (multi-factor NeuralProphet model, MF-NPM) considering multiple factors was constructed by taking solar activity index, geomagnetic activity index, geographic coordinates, and IGS GIM data as input parameters. Data from 2009 to 2013 were used to train the model to achieve forecasts of regional ionospheric TEC at different latitudes during the solar maximum phase (2014) and geomagnetic storms by sliding 1 day. In order to verify the prediction performance of the MF-NPM, the multi-factor long short-term memory neural network (LSTMNN) model was also constructed for comparative analysis. At the same time, the TEC prediction results of the two models were compared with the IGS GIM and CODE 1-day predicted GIM products (COPG_P1). The results show that the MF-NPM achieves good prediction performance effectively. The RMSE and relative accuracy (RA) of MF-NPM are 2.33 TECU and 93.75%, respectively, which are 0.77 and 1.87 TECU and 1.91% and 6.68% better than LSTMNN and COPG_P1 in the solar maximum phase (2014). During the geomagnetic storm, the RMSE and RA of TEC prediction results based on the MF-NPM are 3.12 TECU and 92.86%, respectively, which are improved by 1.25 and 2.30 TECU and 2.38% and 7.24% compared with LSTMNN and COPG_P1. Furthermore, the MF-NPM also achieves better performance in low–mid latitudes. Full article

(This article belongs to the Special Issue Beidou/GNSS Precise Positioning and Atmospheric Modeling II)

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26 pages, 22782 KiB

Open AccessArticle

Spatial Estimation of Regional PM_2.5 Concentrations with GWR Models Using PCA and RBF Interpolation Optimization

by Youbing Tang, Shaofeng Xie, Liangke Huang, Lilong Liu, Pengzhi Wei, Yabo Zhang and Chunyang Meng

Remote Sens. 2022, 14(21), 5626; https://doi.org/10.3390/rs14215626 - 7 Nov 2022

Cited by 13 | Viewed by 2353

Abstract

In recent years, geographically weighted regression (GWR) models have been widely used to address the spatial heterogeneity and spatial autocorrelation of PM_2.5, but these studies have not fully considered the effects of all potential variables on PM_2.5 variation and have rarely optimized the models for residuals. Therefore, we first propose a modified GWR model based on principal component analysis (PCA-GWR), then introduce five different spatial interpolation methods of radial basis functions to correct the residuals of the PCA-GWR model, and finally construct five combinations of residual correction models to estimate regional PM_2.5 concentrations. The results show that (1) the PCA-GWR model can fully consider the contributions of all potential explanatory variables to estimate PM_2.5 concentrations and minimize the multicollinearity among explanatory variables, and the PM_2.5 estimation accuracy and the fitting effect of the PCA-GWR model are better than the original GWR model. (2) All five residual correction combination models can better achieve the residual correction optimization of the PCA-GWR model, among which the PCA-GWR model corrected by Multiquadric Spline (MS) residual interpolation (PCA-GWRMS) has the most obvious accuracy improvement and more stable generalizability at different time scales. Therefore, the residual correction of PCA-GWR models using spatial interpolation methods is effective and feasible, and the results can provide references for regional PM_2.5 spatial estimation and spatiotemporal mapping. (3) The PM_2.5 concentrations in the study area are high in winter months (January, February, December) and low in summer months (June, July, August), and spatially, PM_2.5 concentrations show a distribution of high north and low south. Full article

(This article belongs to the Special Issue Beidou/GNSS Precise Positioning and Atmospheric Modeling II)

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14 pages, 25942 KiB

Open AccessArticle

Tropospheric Second-Order Horizontal Gradient Modeling for GNSS PPP

by Yaozong Zhou, Yidong Lou, Weixing Zhang, Peida Wu, Jingna Bai and Zhenyi Zhang

Remote Sens. 2022, 14(19), 4807; https://doi.org/10.3390/rs14194807 - 26 Sep 2022

Cited by 3 | Viewed by 1610

Abstract

The asymmetric delay has a considerable impact on Global Navigation Satellite Systems (GNSS) Positioning, Navigation and Timing (PNT) applications. In GNSS analyses, the impacts of the asymmetric delay are commonly compensated by using the classical methods with considering the north-south and east-west horizontal gradients. In this paper, we have initiatively proposed an extended method where the north-south and east-west horizontal gradients as well as the second-order horizontal gradients are included to better fit the asymmetric delay. The modeling accuracy of the extended method was evaluated at globally distributed 905 GNSS stations during 40 days in 2020. Significant performance of the extended method respect to the classical method was found, where the hydrostatic and wet modeling accuracy at 4° elevation angle was improved from 5.3 and 10.6 mm to 1.6 and 4.9 mm by 70% and 54%, respectively. The GNSS Precise Point Positioning (PPP) performance using the extended method was also validated at 107 Multi-GNSS Experiment (MGEX) stations. The superior performance on the coordinate repeatability and significant effectiveness on the coordinate and Zenith Total Delay (ZTD) estimations were also found, and the maximal vertical (U) coordinate and ZTD difference biases reached 8.6 and −4.5 mm. The extended method is therefore recommended to substitute the classical methods in the GNSS analyses, especially under severe atmospheric conditions. Full article

(This article belongs to the Special Issue Beidou/GNSS Precise Positioning and Atmospheric Modeling II)

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