scholarly journals A Robust Method for GPS/BDS Pseudorange Differential Positioning Based on the Helmert Variance Component Estimation

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Jian Deng ◽  
Xingwang Zhao ◽  
Aiguo Zhang ◽  
Fuyang Ke
Keyword(s):  
Real Time ◽  
Variance Component ◽  
Large Deviation ◽  
Satellite System ◽  
Observation Data ◽  
Variance Component Estimation ◽  
Relative Positioning ◽  
Long Baseline ◽  
Component Estimation ◽  
Global Navigation Satellite

The use of global navigation satellite system (GNSS) is entering a new era of joint positioning based on the use of multifrequencies and multimodes. Ensuring the correct weighting of observations from each system and satellite has become a key problem during real-time positioning. This paper addresses the issue of weights of observations as well as the quality control of GPS/BDS pseudoranges in the context of real-time relative positioning. Thus, in the first place, the Helmert variance component estimation (VCE) is used to determine the relative weighting of observations from the two systems, and then, we introduce robustness estimation theory and construct a new method. The method is resistant to the influence of outliers in the observations by selecting weight iterations. To do this, we selected GPS/BDS observation data at baseline lengths of 40 km, 46 km, and 64 km for verification and analysis. Experimental results show that, in terms of the relative positioning of medium-to-long baseline based on GPS/BDS pseudorange observations, when observed values incorporate large gross errors, our method can reduce the weighting of suspicious or abnormal values and weaken their impact on positioning solutions, so that the positioning results will not appear to have large deviation.

GPS-BDS-Galileo double-differenced stochastic model refinement based on least-squares variance component estimation

2021 ◽  
pp. 1-16
Author(s):  
Hong Hu ◽  
Xuefeng Xie ◽  
Jingxiang Gao ◽  
Shuanggen Jin ◽  
Peng Jiang
Keyword(s):  
Stochastic Model ◽  
Least Squares ◽  
Stochastic Models ◽  
Variance Component ◽  
Satellite System ◽  
Variance Component Estimation ◽  
Short Baseline ◽  
Component Estimation ◽  
Zero Baseline ◽  
Global Navigation Satellite

Abstract Stochastic models are essential for precise navigation and positioning of the global navigation satellite system (GNSS). A stochastic model can influence the resolution of ambiguity, which is a key step in GNSS positioning. Most of the existing multi-GNSS stochastic models are based on the GPS empirical model, while differences in the precision of observations among different systems are not considered. In this paper, three refined stochastic models, namely the variance components between systems (RSM1), the variances of different types of observations (RSM2) and the variances of observations for each satellite (RSM3) are proposed based on the least-squares variance component estimation (LS-VCE). Zero-baseline and short-baseline GNSS experimental data were used to verify the proposed three refined stochastic models. The results show that, compared with the traditional elevation-dependent model (EDM), though the proposed models do not significantly improve the ambiguity resolution success rate, the positioning precision of the three proposed models has been improved. RSM3, which is more realistic for the data itself, performs the best, and the precision at elevation mask angles 20°, 30°, 40°, 50° can be improved by 4⋅6%, 7⋅6%, 13⋅2%, 73⋅0% for L1-B1-E1 and 1⋅1%, 4⋅8%, 16⋅3%, 64⋅5% for L2-B2-E5a, respectively.

scholarly journals Online Near real-time Mine Disaster Monitoring System Based on Geosensor Networks

2016 ◽  
Vol 12 (03) ◽  
pp. 64
Author(s):  
Haifeng Hu
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Satellite System ◽  
Open Pit ◽  
Observation Data ◽  
Complex Data ◽  
Disaster Monitoring ◽  
Process Observation ◽  
Global Navigation Satellite ◽  
Safety And Stability

Abstract—An online automatic disaster monitoring system can reduce or prevent geological mine disasters to protect life and property. Global Navigation Satellite System receivers and the GeoRobot are two kinds of in-situ geosensors widely used for monitoring ground movements near mines. A combined monitoring solution is presented that integrates the advantages of both. In addition, a geosensor network system to be used for geological mine disaster monitoring is described. A complete online automatic mine disaster monitoring system including data transmission, data management, and complex data analysis is outlined. This paper proposes a novel overall architecture for mine disaster monitoring. This architecture can seamlessly integrate sensors for long-term, remote, and near real-time monitoring. In the architecture, three layers are used to collect, manage and process observation data. To demonstrate the applicability of the method, a system encompassing this architecture has been deployed to monitor the safety and stability of a slope at an open-pit mine in Inner Mongolia.

scholarly journals Helmert Variance Component Estimation for Multi-GNSS Relative Positioning

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 669 ◽  
Author(s):  
Mowen Li ◽  
Wenfeng Nie ◽  
Tianhe Xu ◽  
Adria Rovira-Garcia ◽  
Zhenlong Fang ◽  
...  
Keyword(s):  
Variance Component ◽  
Computation Time ◽  
Satellite System ◽  
Unit Weight ◽  
Variance Component Estimation ◽  
Positioning Accuracy ◽  
Gnss Positioning ◽  
Component Estimation ◽  
Weighting Strategy ◽  
Gnss Constellation

The Multi-constellation Global Navigation Satellite System (Multi-GNSS) has become the standard implementation of high accuracy positioning and navigation applications. It is well known that the noise of code and phase measurements depend on GNSS constellation. Then, Helmert variance component estimation (HVCE) is usually used to adjust the contributions of different GNSS constellations by determining their individual variances of unit weight. However, HVCE requires a heavy computation load. In this study, the HVCE posterior weighting was employed to carry out a kinematic relative Multi-GNSS positioning experiment with six short-baselines from day of year (DoY) 171 to 200 in 2019. As a result, the HVCE posterior weighting strategy improved Multi-GNSS positioning accuracy by 20.5%, 15.7% and 13.2% in east-north-up (ENU) components, compared to an elevation-dependent (ED) priori weighting strategy. We observed that the weight proportion of both code and phase observations for each GNSS constellation were consistent during the entire 30 days, which indicates that the weight proportions of both code and phase observations are stable over a long period of time. It was also found that the quality of a phase observation is almost equivalent in each baseline and GNSS constellation, whereas that of a code observation is different. In order to reduce the time consumption of the HVCE method without sacrificing positioning accuracy, the stable variances of unit weights of both phase and code observations obtained over 30 days were averaged and then frozen as a priori information in the positioning experiment. The result demonstrated similar ENU improvements of 20.0%, 14.1% and 11.1% with respect to the ED method but saving 88% of the computation time of the HCVE strategy. Our study concludes with the observations that the frozen variances of unit weight (FVUW) could be applied to the positioning experiment for the next 30 days, that is, from DoY 201 to 230 in 2019, improving the positioning ENU accuracy of the ED method by 18.1%, 13.2% and 10.6%, indicating the effectiveness of the FVUW.

An adaptive Kalman filter based on variance component estimation for a real-time ZTD solution

2019 ◽  
Vol 54 (1) ◽  
pp. 89-121 ◽  
Author(s):  
Xu Yang ◽  
Guobin Chang ◽  
Qianxin Wang ◽  
Shubi Zhang ◽  
Ya Mao ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Variance Component ◽  
Variance Component Estimation ◽  
Adaptive Kalman Filter ◽  
Component Estimation

scholarly journals ADJUSTMENT OF CADASTRAL NETWORK USING LEAST-SQUARES VARIANCE COMPONENT ESTIMATION

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 161-167
Author(s):  
N. K. Bidi ◽  
A. H. M. Din ◽  
Z. A. M. Som ◽  
A. H. Omar
Keyword(s):  
Stochastic Model ◽  
Least Squares ◽  
Variance Components ◽  
Variance Component ◽  
Geodetic Network ◽  
Observation Data ◽  
Variance Component Estimation ◽  
Station Coordinates ◽  
Component Estimation ◽  
Estimation Of Variance

Abstract. The role of the stochastic model very important in data processing of geodetic network since it describes the accuracy of the measurements and their correlation with each other. Knowledge of weights of the observables is required to provide a better understanding of the sources of errors and to model the error, hence the weights need to be determined correctly. This study concentrates on the estimation of variance components from different types of instruments used in the cadastral survey. The ideas are to combine the conventional and advanced instruments in a traverse network to enhance the estimated variance component in the stochastic model. Thus, Least Squares Variance Component Estimation (LS-VCE) method was used in this study because the method is simple, flexible and attractive due to the precision of variance estimators that can be directly obtained. Observation data come with several types of instruments such as chain measurement, Electronic Distance Measurement and total station were utilized. The findings showed that LS-VCE method was very reliable in cadastral network application. Besides, the results revealed that the estimated variance components for distance scale error, σp seem to become unrealistic for each data tested. It was found that the traverse network which included chain survey, showed the insignificant result to the precision of station coordinates when the measurements were combined.

scholarly journals Improving the Performance of Multi-GNSS Time and Frequency Transfer Using Robust Helmert Variance Component Estimation

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2878 ◽  
Author(s):  
Pengfei Zhang ◽  
Rui Tu ◽  
Yuping Gao ◽  
Rui Zhang ◽  
Na Liu
Keyword(s):  
Variance Component ◽  
Global Navigation Satellite Systems ◽  
Variance Component Estimation ◽  
Satellite Systems ◽  
Component Estimation ◽  
The Mean ◽  
Frequency Transfer ◽  
Clock Estimation ◽  
Global Navigation Satellite ◽  
Different Characteristics

The combination of multiple Global Navigation Satellite Systems (GNSSs) may improve the performance of time and frequency transfers by increasing the number of available satellites and improving the time dilution of precision. However, the receiver clock estimation is easily affected by the inappropriate weight of multi-GNSSs due to the different characteristics of individual GNSS signals as well as the outliers from observations. Thus, we utilised a robust Helmert variance component estimation (RVCE) approach to determine the appropriate weights of different GNSS observations, and to control for the influence of outliers in these observation in multi-GNSS time and frequency transfer. In order to validate the effectiveness of this approach, four time links were employed. Compared to traditional solutions, the mean improvement of smoothed residuals is 3.43% using the RVCE approach. With respect to the frequency stability of the time links, the RVCE solution outperforms the traditional solution, particularly in the short-term, and the mean improvement is markedly high at 14.89%.

Development of 10-minute interval analysis and prediction system in KMA

2020 ◽  
Author(s):  
Minyou Kim ◽  
Keunhee Lee ◽  
Yong Hee Lee
Keyword(s):  
Real Time ◽  
Interval Analysis ◽  
Short Range ◽  
Satellite System ◽  
Precipitation Forecast ◽  
Local Analysis ◽  
Observation Data ◽  
Prediction System ◽  
Minute Interval ◽  
Global Navigation Satellite

<p>To be well prepared for rapidly-developing meteorological hazards in advance, quick and qualified information on real-time and very-short range (within 6 hours) forecasts is required. KLAPS (Korea Local Analysis and Prediction System) was developed for the operational very-short range forecasts in KMA (Korea Meteorological Administration), based on the LAPS (Local Analysis and Prediction System) from NOAA and WRF from NCAR in 2009. Recently, KLAPS is updated to use new observation datasets and physics schemes from KIM (Korea Integrated Model) to improve its very-short range precipitation forecast skills. New observation data sources (geostationary satellite, RADAR, ground-based GNSS(Global Navigation Satellite System), ceilometer, local radiosonde, etc.) are ingested into KLAPS in real-time to resolve rapidly developing mesoscale systems. Physics schemes (WDM7, KSAS(Kiaps SAS), RRTMG, Shing-Hong PBL, etc.) based on KIM physics package are implemented in KLAPS to support the high-resolution physics. The new KLAPS is now operated in 10-minute interval, so that it could provide 10-minute interval precipitation forecasts to the public(www.weather.go.kr) every 10 minutes. The advantages of 10-minute interval analysis and forecast system will be presented.</p>

scholarly journals Accuracy Analysis of GNSS Hourly Ultra-Rapid Orbit and Clock Products from SHAO AC of iGMAS

2021 ◽  
Vol 13 (5) ◽  
pp. 1022
Author(s):  
Qinming Chen ◽  
Shuli Song ◽  
Weili Zhou
Keyword(s):  
Real Time ◽  
Satellite System ◽  
High Accuracy ◽  
Observation Data ◽  
Navigation Satellite ◽  
International Gnss Service ◽  
Observation Session ◽  
New Strategy ◽  
Analysis Center ◽  
Global Navigation Satellite

With the development of the global navigation satellite system(GNSS), the hourly ultra-rapid products of GNSS are attracting more attention due to their low latency and high accuracy. A new strategy and method was applied by the Shanghai Astronomical Observatory (SHAO) Analysis Center (AC) of the international GNSS Monitoring and Assessment Service (iGMAS) for generating 6-hourly and 1-hourly GNSS products, which mainly include the American Global Positioning System (GPS), the Russian Global’naya Navigatsionnaya Sputnikova Sistema (GLONASS), the European Union’s Galileo, and the Chinese BeiDou navigation satellite system (BDS). The 6-hourly and 1-hourly GNSS orbit and clock ultra-rapid products included a 24-h observation session which is determined by 24-h observation data from global tracking stations, and a 24-h prediction session which is predicted from the observation session. The accuracy of the 1-hourly orbit product improved about 1%, 31%, 13%, 11%, 23%, and 9% for the observation session and 18%, 43%, 45%, 34%, 53%, and 15% for the prediction session of GPS, GLONASS, Galileo, BDS Medium Earth Orbit (MEO), Inclined Geosynchronous Orbit (IGSO), and GEO orbit, when compared with reference products with high accuracy from the International GNSS service (IGS).The precision of the 1-hourly clock products can also be seen better than the 6-hourly clock products. The accuracy and precision of the 6-hourly and 1-hourly orbit and clock verify the availability and reliability of the hourly ultra-rapid products, which can be used for real-time or near-real-time applications, and show encouraging prospects.

scholarly journals Methodology for the Correction of the Spatial Orientation Angles of the Unmanned Aerial Vehicle Using Real Time GNSS, a Shoreline Image and an Electronic Navigational Chart

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2810
Author(s):  
Krzysztof Naus ◽  
Piotr Szymak ◽  
Paweł Piskur ◽  
Maciej Niedziela ◽  
Aleksander Nowak
Keyword(s):  
Real Time ◽  
Spatial Orientation ◽  
Orientation Angle ◽  
Satellite System ◽  
Angle Measurement ◽  
Angle Correction ◽  
Lidar Measurements ◽  
Aerial Vehicle ◽  
Marine Applications ◽  
Global Navigation Satellite

Undoubtedly, Low-Altitude Unmanned Aerial Vehicles (UAVs) are becoming more common in marine applications. Equipped with a Global Navigation Satellite System (GNSS) Real-Time Kinematic (RTK) receiver for highly accurate positioning, they perform camera and Light Detection and Ranging (LiDAR) measurements. Unfortunately, these measurements may still be subject to large errors-mainly due to the inaccuracy of measurement of the optical axis of the camera or LiDAR sensor. Usually, UAVs use a small and light Inertial Navigation System (INS) with an angle measurement error of up to 0.5∘ (RMSE). The methodology for spatial orientation angle correction presented in the article allows the reduction of this error even to the level of 0.01∘ (RMSE). It can be successfully used in coastal and port waters. To determine the corrections, only the Electronic Navigational Chart (ENC) and an image of the coastline are needed.

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