scholarly journals A New GPT2w Model Improved by PSO-LSSVM for GNSS High-Precision Positioning

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Xuanxuan Zhang ◽  
Yamin Dang ◽  
Changhui Xu
Keyword(s):  
Time Series ◽  
High Precision ◽  
Meteorological Parameters ◽  
Meteorological Parameter ◽  
Support Vector ◽  
Tropospheric Delay ◽  
Zenith Tropospheric Delay ◽  
Station Coordinates ◽  
Short Period ◽  
Gpt2w Model

Tropospheric delay is an important error affecting GNSS high-precision navigation and positioning, which will decrease the precision of navigation and positioning if it is not well corrected. Actually, tropospheric delay, especially in the zenith direction, is related to a series of meteorological parameters, such as temperature and pressure. To estimate the zenith tropospheric delay (ZTD) as accurately as possible, the paper proposes a new fused model using the least squares support vector machines (LSSVM) and the particle swarm optimization (PSO) to improve the precision and temporal resolution of meteorological parameters in global pressure and temperature 2 wet (GPT2w). The proposed model uses the time series of meteorological parameters from the GPT2w model as the initial value, and thus, the time series of the residuals can be obtained between the meteorological parameters from meteorological sensors (MS) and the GPT2w model. The long time series of meteorological parameters is the evident periodic signal. The GPT2w model describes its dominant frequency (harmonics), and the residuals thus can be seen as the short-period signal (nonharmonics). The combined PSO and LSSVM model (PSO-LSSVM) is used to predict the specific value of the short-period signal. The new GPT2w model, in which the meteorological parameter value is obtained by combining the estimated meteorological parameters residuals and the GPT2w-derived meteorological parameters, can be acquired. The GNSS network stations in Hong Kong throughout 2017-2018 are processed by the GNSS Processing and Analysis Software (GPAS), which is developed by the Chinese Academy of Surveying & Mapping, to estimate the zenith tropospheric delay and station coordinates using the new GPT2w model. Statistical results reveal that the accuracy of the new GPT2w model-derived ZTD was improved by 60% or more compared with that of the GPT2w-derived ZTD. In addition, the positioning accuracy of the GNSS station has been effectively improved up to 44.89%. Such results reveal that the new GPT2w model can greatly reduce the influence of nonharmonic components (short-period terms) of the meteorological parameter time series and achieve better accuracy than the GPT2w model.

scholarly journals Regional Zenith Tropospheric Delay Modeling Based on Least Squares Support Vector Machine Using GNSS and ERA5 Data

2021 ◽  
Vol 13 (5) ◽  
pp. 1004
Author(s):  
Song Li ◽  
Tianhe Xu ◽  
Nan Jiang ◽  
Honglei Yang ◽  
Shuaimin Wang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
High Efficiency ◽  
Rapid Development ◽  
Support Vector ◽  
Tropospheric Delay ◽  
Improvement Rate ◽  
Zenith Tropospheric Delay ◽  
Background Data ◽  
Mean Square Errors

The meteorological reanalysis data has been widely applied to derive zenith tropospheric delay (ZTD) with a high spatial and temporal resolution. With the rapid development of artificial intelligence, machine learning also begins as a high-efficiency tool to be employed in modeling and predicting ZTD. In this paper, we develop three new regional ZTD models based on the least squares support vector machine (LSSVM), using both the International GNSS Service (IGS)-ZTD products and European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) data over Europe throughout 2018. Among them, the ERA5 data is extended to ERA5S-ZTD and ERA5P-ZTD as the background data by the model method and integral method, respectively. Depending on different background data, three schemes are designed to construct ZTD models based on the LSSVM algorithm, including the without background data, with the ERA5S-ZTD, and with the ERA5P-ZTD. To investigate the advantage and feasibility of the proposed ZTD models, we evaluate the accuracy of two background data and three schemes by segmental comparison with the IGS-ZTD of 85 IGS stations in Europe. The results show that the overall average Root Mean Square Errors (RMSE) value of all sites is 30.1 mm for the ERA5S-ZTD, and 10.7 mm for the ERA5P-ZTD. The overall average RMSE is 25.8 mm, 22.9 mm, and 9 mm for the three schemes, respectively. Moreover, the overall improvement rate is 19.1% and 1.6% for the ZTD model with ERA5S-ZTD and ERA5P-ZTD, respectively. In order to explore the reason of the lower improvement for the ZTD model with ERA5P-ZTD, the loop verification is performed by estimating the ZTD values of each available IGS station. In actuality, the monthly improvement rate of estimated ZTD is positive for most stations, and the biggest improvement rate can even reach about 40%. The negative rate mainly comes from specific stations, these stations are located on the edge of the region, near the coast, as well as the lower similarity between the individual verified station and training stations.

scholarly journals Estimating Zenith Tropospheric Delay Based on GPT2w Model

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 139258-139263
Author(s):  
Zan Liu ◽  
Xihong Chen ◽  
Qiang Liu
Keyword(s):  
Tropospheric Delay ◽  
Zenith Tropospheric Delay ◽  
Gpt2w Model

ANALYSIS OF RADON TIME SERIES RECORDED IN SLOVAK AND CZECH CAVES FOR THE DETECTION OF ANOMALIES DUE TO SEISMIC PHENOMENA

2019 ◽  
Vol 186 (2-3) ◽  
pp. 428-432 ◽  
Author(s):  
Fabrizio Ambrosino ◽  
Lenka Thinová ◽  
Miloš Briestenský ◽  
Carlo Sabbarese
Keyword(s):  
Time Series ◽  
Continuous Monitoring ◽  
Meteorological Parameters ◽  
Activity Concentration ◽  
Support Vector ◽  
Mathematical Methods ◽  
Tectonic Structures ◽  
Radon Activity ◽  
Mode Decomposition ◽  
Active Tectonic

Abstract Anomalies in the radon (222Rn) releases in underground environments are one of the phenomena that can be observed before earthquake occurrence. Continuous measurements of radon activity concentration, and of meteorological parameters that influence the gas emission, were performed in three Slovak and Czech caves during 1-y period (1 July 2016–30 June 2017). The radon activity concentration in caves shows seasonal variations, with maxima reached during summer months. The anomalies in the radon time series are identified using a combination of three mathematical methods: multiple linear regression, empirical mode decomposition and support vector regression. The radon anomaly periods were compared with earthquake occurrences in Europe. Coincidences between both phenomena were found, since all monitored caves reflect contemporaneous local tectonic changes. The results indicate that radon continuous monitoring could assist a better understanding of radon emissions, along active tectonic structures, during seismic events.

scholarly journals RESEARCH ON ZENITH TROPOSPHERIC DELAY MODELING OF REGIONAL CORS NETWORK

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 1197-1200
Author(s):  
Y. F. Yang ◽  
X. P. Chen ◽  
M. H. Yao ◽  
C. L. Zhou ◽  
C. M. Liao
Keyword(s):  
High Precision ◽  
Reference Values ◽  
Negative Correlation ◽  
Reference Value ◽  
Tropospheric Delay ◽  
Guangxi Province ◽  
New Model ◽  
Zenith Tropospheric Delay ◽  
The Relationship

Abstract. By calculating the zenith troposphere information from 11 reference stations of the CORS network in Guilin City, Guangxi Province in 2018 by GAMIT10.6 as the reference values, analyzing the relationship between the zenith troposphere and the elevation, as well as the latitude in the Guilin Region, building a model for the zenith tropospheric delay (ZTD) suitable for the Guilin Region, uniformly selecting 8 CORS reference stations in the Guilin Region to build a new model, comparing with the ZTD estimated by GAMIT10.6 and studying the applicability of the new model in the Guilin Region, the results showed that: 1) In the Guilin Region, the ZTD presented linear negative correlation with the station elevation; 2) the ZTD estimated by the new model was well consistent with the reference value, with high precision, and increased with the elevation.

scholarly journals The Impact of Different Mapping Function Models and Meteorological Parameter Calculation Methods on the Calculation Results of Single-Frequency Precise Point Positioning with Increased Tropospheric Gradient

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Ying Liu ◽  
Ren Wang ◽  
Jingxiang Gao ◽  
Peng Zhu
Keyword(s):  
Meteorological Parameters ◽  
Meteorological Parameter ◽  
Mapping Function ◽  
Single Frequency ◽  
Tropospheric Delay ◽  
Calculation Methods ◽  
Function Model ◽  
Parameter Calculation ◽  
Gradient Model ◽  
Function Models

Tropospheric delay is one of the main errors in precise point positioning (PPP). The inaccuracy of the tropospheric delay model will inevitably lead to a decrease in PPP accuracy. Therefore, the influence of the tropospheric gradient on the positioning accuracy should be considered in the processing of tropospheric delay. At the same time, the effects of different mapping function models and meteorological parameter calculation methods on the tropospheric delay accuracy of single-frequency PPP (SF PPP) are analyzed. Twelve MGEX stations, which are evenly distributed in the world, are used in this article. Taking into account the seasonal variation of the tropospheric delay, the observation times adopted are 2016, 2017, and 2018 for different seasons (winter, day of year (DOY): 22–28; spring, DOY: 92–98; summer, DOY: 199–205; and autumn, DOY: 275–281). Then, according to different mapping function models and meteorological parameter calculation methods, a total of 7056 tests and 9072 tests are performed, respectively. The following results were obtained after comparative analysis. (1) When the same method is used for calculating meteorological parameters, the percentage with improved tropospheric delay repeatability calculated by the Hopfield mapping function model (MFM3) is the highest, reaching more than 70%, and by Vienna Mapping Functions 3 (VMF3, grid resolution is 1°), the mapping function model (MFM8) is the lowest, less than 67.5%. The percentage with improved position repeatability is highest in the north (N) direction and lowest in the up (U) direction. (2) Using the same mapping function model, the correction of the tropospheric gradient model has a greater impact on calculating the repeatability percentage of the tropospheric delay and the position. Compared with standard atmospheric parameters, other calculation methods of meteorological parameters have little effect on the percentage increase of the tropospheric delay value and the positioning result after adding the tropospheric gradient model. It shows that different calculation methods of meteorological parameters have little effect on the calculation of tropospheric delay and position, different mapping function models have a large effect on the calculation of tropospheric delay and position, and the tropospheric gradient model has the greatest influence on the calculation of tropospheric delay and position.

scholarly journals A New Zenith Tropospheric Delay Grid Product for Real-Time PPP Applications over China

Sensors ◽  
2017 ◽  
Vol 18 (2) ◽  
pp. 65 ◽  
Author(s):  
Yidong Lou ◽  
Jinfang Huang ◽  
Weixing Zhang ◽  
Hong Liang ◽  
Fu Zheng ◽  
...  
Keyword(s):  
Real Time ◽  
Tropospheric Delay ◽  
Zenith Tropospheric Delay
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