scholarly journals Improving the Stochastic Model for VRS Network-Based GNSS Surveying

2019 ◽  
Vol 54 (1) ◽  
pp. 17-30 ◽  
Author(s):  
Thanate Jongrujinan ◽  
Chalermchon Satirapod
Keyword(s):  
Stochastic Model ◽  
Covariance Matrix ◽  
Ambiguity Resolution ◽  
Reference Station ◽  
Double Difference ◽  
Atmospheric Effects ◽  
Equal Weight ◽  
Virtual Reference ◽  
Positioning Accuracy ◽  
Variance Covariance Matrix

Abstract The VRS network-based technique has become the main precise GNSS surveying method especially for medium-range baselines (approximately 20-70 km). The key concept of this approach is to use the observables of multiple reference stations to generate the network correction in the form of a virtual reference station for mitigating distance-dependent errors including atmospheric effects and orbital uncertainty at the user’s location. Numerous GNSS data processing strategies have been adopted in the functional model in order to improve both the positioning accuracy and the success of ambiguity resolution. However, it is impossible to completely model the aforementioned errors. As a result, the unmodelled residuals still remain in the virtual reference station observables when the least squares estimation is employed. An alternative approach to deal with these residuals is to construct a more realistic stochastic model whereby the variance-covariance matrix is assumed to be homoscedastic. This research aims to investigate a suitable stochastic model used for the VRS technique. The rigorous statistical method, MINQUE has been applied to estimate the variance-covariance matrix of the double-difference observables for a virtual reference station to rover baseline determination. The findings of the comparison to the equal-weight model and the satellite elevation-based model indicated that the MINQUE procedure could enhance the positioning accuracy. In addition, the reliability of ambiguity resolution is also improved.

Stochastic modeling for VRS network-based GNSS RTK with residual interpolation uncertainty

2020 ◽  
Vol 14 (3) ◽  
pp. 317-325
Author(s):  
Thanate Jongrujinan ◽  
Chalermchon Satirapod
Keyword(s):  
Stochastic Model ◽  
Ambiguity Resolution ◽  
Functional Model ◽  
Integer Ambiguity ◽  
Reference Station ◽  
Unbiased Estimation ◽  
Atmospheric Effects ◽  
Virtual Reference ◽  
Positioning Accuracy ◽  
Comparison Results

AbstractThe key concept of the virtual reference station (VRS) network-based technique is to use the observables of multiple reference stations to generate the network corrections in the form of a virtual reference station at a nearby user’s location. Regarding the expected positioning accuracy, the novice GNSS data processing strategies have been adopted in the server-side functional model for mitigating distance-dependent errors including atmospheric effects and orbital uncertainty in order to generate high-quality virtual reference stations. In addition, the realistic stochastic model also plays an important role to take account of the unmodelled error in the rover-side processing. The results of our previous study revealed that the minimum norm quadratic unbiased estimation (MINQUE) stochastic model procedure can improve baseline component accuracy and integer ambiguity reliability, however, it requires adequate epoch length in a solution to calculate the elements of the variance-covariance matrix. As a result, it may not be suitable for urban environment where the satellite signal interruptions take place frequently, therefore, the ambiguity resolution needs to be resolved within the limited epochs. In order to address this limitation, this study proposed the stochastic model based on using the residual interpolation uncertainty (RIU) as the weighting schemes. This indicator reflects the quality of network corrections for any satellite pair at a specific rover position and can be calculated on the epoch-by-epoch basis. The comparison results with the standard stochastic model indicated that the RIU-weight model produced slightly better positioning accuracy but increased significant level of the ambiguity resolution successful rate.

scholarly journals A Virtualization Approach to Correct Systematic Errors in Measured TDOA and FDOA for Low Orbit Dual-Satellite Positioning Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Gang Li ◽  
Min Zhou ◽  
Hongwen Tang ◽  
Hongbin Chen
Keyword(s):  
Systematic Errors ◽  
Time Difference ◽  
Frequency Difference ◽  
Reference Station ◽  
Virtual Reference ◽  
Time Difference Of Arrival ◽  
Positioning Accuracy ◽  
Positioning Systems ◽  
Location System ◽  
Measured Time

The low-orbit dual-satellite passive location system provides a cost-efficient and easy implementation platform, by which positions of unknown emitters on the Earth can be determined through measuring both the time and the frequency differences by two low-orbit satellites in space. However, in reality, this dual-satellite location system has low positioning accuracy because of the existence of systematic errors. In this paper, in order to address the problem of low positioning accuracy in low-orbit dual-satellite systems, a virtualization approach, consisting of the establishment of the virtual reference station and virtual frequency conversion, is proposed to correct systematic errors in the system. Specifically, we first analyze the coming source of systematic errors in the dual-satellite location system, and then, a virtual reference station and virtual frequency are constructed to correct errors in the measured time difference of arrival and the frequency difference of arrival, respectively. Simulation results show that systematic errors caused by the measured time difference of arrival can be significantly reduced, and the correction efficiency, defined as a ratio between remaining errors after implementing the proposed method over uncorrected ones, for the measured frequency difference of arrival, largely relies on both the virtual frequency and the transmission frequency of reference stations.

scholarly journals A New Variance-Covariance Matrix for Improving Positioning Accuracy in High-Speed GPS Receivers

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7324
Author(s):  
Narjes Rahemi ◽  
Mohammad Reza Mosavi ◽  
Diego Martín
Keyword(s):  
Kalman Filter ◽  
Covariance Matrix ◽  
High Speed ◽  
Dynamic Models ◽  
Unscented Kalman Filter ◽  
Statistical Characteristics ◽  
Spatial Correlations ◽  
Positioning Accuracy ◽  
High Speeds ◽  
Variance Covariance Matrix

One of the main challenges in using GPS is reducing the positioning accuracy in high-speed conditions. In this contribution, by considering the effect of spatial correlation between observations in estimating the covariances, we propose a model for determining the variance–covariance matrix (VCM) that improves the positioning accuracy without increasing the computational load. In addition, we compare the performance of the extended Kalman filter (EKF) and unscented Kalman filter (UKF) combined with different dynamic models, along with the proposed VCM in GPS positioning at high speeds. To review and test the methods, we used six motion scenarios with different speeds from medium to high and examined the positioning accuracy of the methods and some of their statistical characteristics. The simulation results demonstrate that the EKF algorithm based on the Gauss–Markov model, along with the proposed VCM (based on the sinusoidal function and considering spatial correlations), performs better and provides at least 30% improvement in the positioning, compared to the other methods.

scholarly journals ON THE REALISTIC STOCHASTIC MODEL OF GPS OBSERVABLES: IMPLEMENTATION AND PERFORMANCE

2015 ◽  
Vol XL-1-W5 ◽  
pp. 755-761 ◽  
Author(s):  
F. Zangeneh-Nejad ◽  
A. R. Amiri-Simkooei ◽  
M. A. Sharifi ◽  
J. Asgari
Keyword(s):  
Stochastic Model ◽  
Success Rate ◽  
High Precision ◽  
Ambiguity Resolution ◽  
Temporal Correlation ◽  
Noise Model ◽  
Integer Ambiguity ◽  
Double Difference ◽  
Data Sets ◽  
Gps Positioning

High-precision GPS positioning requires a realistic stochastic model of observables. A realistic GPS stochastic model of observables should take into account different variances for different observation types, correlations among different observables, the satellite elevation dependence of observables precision, and the temporal correlation of observables. Least-squares variance component estimation (LS-VCE) is applied to GPS observables using the geometry-based observation model (GBOM). To model the satellite elevation dependent of GPS observables precision, an exponential model depending on the elevation angles of the satellites are also employed. Temporal correlation of the GPS observables is modelled by using a first-order autoregressive noise model. An important step in the high-precision GPS positioning is double difference integer ambiguity resolution (IAR). The fraction or percentage of success among a number of integer ambiguity fixing is called the success rate. A realistic estimation of the GNSS observables covariance matrix plays an important role in the IAR. We consider the ambiguity resolution success rate for two cases, namely a nominal and a realistic stochastic model of the GPS observables using two GPS data sets collected by the Trimble R8 receiver. The results confirm that applying a more realistic stochastic model can significantly improve the IAR success rate on individual frequencies, either on L1 or on L2. An improvement of 20% was achieved to the empirical success rate results. The results also indicate that introducing the realistic stochastic model leads to a larger standard deviation for the baseline components by a factor of about 2.6 on the data sets considered.

Algorithm for VRS Based on Star Structure

2011 ◽  
Vol 90-93 ◽  
pp. 2828-2831
Author(s):  
Cheng Fa Gao ◽  
Xue Feng Shen
Keyword(s):  
Ambiguity Resolution ◽  
Solution Method ◽  
Fixed Time ◽  
Reference Station ◽  
Virtual Reference ◽  
Star Network ◽  
Network Rtk ◽  
Baseline Solution ◽  
Triangular Network ◽  
Star Structure

In view of the deficiency of algorithm for VRS (Virtual Reference Station) based on the triangular network, a novel algorithm for VRS which is based on star network is proposed. Firstly, a kind of baseline solution method of network RTK/VRS based on star structure is established and an ambiguity resolution method is also proposed in this paper. Then further research is done to analyze the algorithm of ionospheric and tropospheric correction separately. Finally, the network ambiguity resolution and correction calculation in both star structure network and traditional triangular network are verified and analyzed through two tests. These tests indicate that the Network RTK (VRS) based on star structure this paper proposed can obviously accelerate the fixed time of network ambiguity resolution, which can be up to 50%, and can achieve higher precision and reliability in the generation of network correction.

scholarly journals Single-epoch RTK performance assessment of tightly combined BDS-2 and newly complete BDS-3

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Wanke Liu ◽  
Mingkui Wu ◽  
Xiaohong Zhang ◽  
Wang Wang ◽  
Wei Ke ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Success Rate ◽  
Ambiguity Resolution ◽  
Satellite System ◽  
Asia Pacific ◽  
Single Frequency ◽  
Navigation Satellite ◽  
Short Baseline ◽  
Positioning Accuracy ◽  
Single Epoch

AbstractThe BeiDou global navigation satellite system (BDS-3) constellation deployment has been completed on June 23, 2020, with a full constellation comprising 30 satellites. In this study, we present the performance assessment of single-epoch Real-Time Kinematic (RTK) positioning with tightly combined BeiDou regional navigation satellite system (BDS-2) and BDS-3. We first investigate whether code and phase Differential Inter-System Biases (DISBs) exist between the legacy B1I/B3I signals of BDS-3/BDS-2. It is discovered that the DISBs are in fact about zero for the baselines with the same or different receiver types at their endpoints. These results imply that BDS-3 and BDS-2 are fully interoperable and can be regarded as one constellation without additional DISBs when the legacy B1I/B3I signals are used for precise relative positioning. Then we preliminarily evaluate the single-epoch short baseline RTK performance of tightly combined BDS-2 and the newly completed BDS-3. The performance is evaluated through ambiguity resolution success rate, ambiguity dilution of precision, as well as positioning accuracy in kinematic and static modes using the datasets collected in Wuhan. Experimental results demonstrate that the current BDS-3 only solutions can deliver comparable ambiguity resolution performance and much better positioning accuracy with respect to BDS-2 only solutions. Moreover, the RTK performance is much improved with tightly combined BDS-3/BDS-2, particularly in challenging or harsh conditions. The single-frequency single-epoch tightly combined BDS-3/BDS-2 solution could deliver an ambiguity resolution success rate of 96.9% even with an elevation cut-off angle of 40°, indicating that the tightly combined BDS-3/BDS-2 could achieve superior RTK positioning performance in the Asia–Pacific region. Meanwhile, the three-dimensional (East/North/Up) positioning accuracy of BDS-3 only solution (0.52 cm/0.39 cm/2.14 cm) in the kinematic test is significantly better than that of the BDS-2 only solution (0.85 cm/1.02 cm/3.01 cm) due to the better geometry of the current BDS-3 constellation. The tightly combined BDS-3/BDS-2 solution can provide the positioning accuracy of 0.52 cm, 0.22 cm, and 1.80 cm, respectively.

scholarly journals Characterization of Carrier Phase-Based Positioning in Real-World Jamming Conditions

2021 ◽  
Vol 13 (14) ◽  
pp. 2680
Author(s):  
Søren Skaarup Larsen ◽  
Anna B. O. Jensen ◽  
Daniel H. Olesen
Keyword(s):  
Real World ◽  
Carrier Phase ◽  
Reference Station ◽  
Baseline Length ◽  
Dual Frequency ◽  
Positioning Accuracy ◽  
The Impact ◽  
Single Versus ◽  
Selection Of

GNSS signals arriving at receivers at the surface of the Earth are weak and easily susceptible to interference and jamming. In this paper, the impact of jamming on the reference station in carrier phase-based relative baseline solutions is examined. Several scenarios are investigated in order to assess the robustness of carrier phase-based positioning towards jamming. Among others, these scenarios include a varying baseline length, the use of single- versus dual-frequency observations, and the inclusion of the Galileo and GLONASS constellations to a GPS only solution. The investigations are based on observations recorded at physical reference stations in the Danish TAPAS network during actual jamming incidents, in order to realistically evaluate the impact of real-world jamming on carrier phase-based positioning accuracy. The analyses performed show that, while there are benefits of using observations from several frequencies and constellations in positioning solutions, special care must be taken in solution processing. The selection of which GNSS constellations and observations to include, as well as when they are included, is essential, as blindly adding more jamming-affected observations may lead to worse positioning accuracy.

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