scholarly journals Improvement of Multi-GNSS Precision and Success Rate Using Realistic Stochastic Model of Observations

2021 ◽  
Vol 14 (1) ◽  
pp. 60
Author(s):  
Farinaz Mirmohammadian ◽  
Jamal Asgari ◽  
Sandra Verhagen ◽  
Alireza Amiri-Simkooei
Keyword(s):  
Stochastic Model ◽  
Data Processing ◽  
Success Rate ◽  
Global Navigation Satellite Systems ◽  
Integer Ambiguity ◽  
Double Difference ◽  
Unbiased Estimation ◽  
Data Sets ◽  
Short Baseline ◽  
Gnss Data

With the advancement of multi-constellation and multi-frequency global navigation satellite systems (GNSSs), more observations are available for high precision positioning applications. Although there is a lot of progress in the GNSS world, achieving realistic precision of the solution (neither too optimistic nor too pessimistic) is still an open problem. Weighting among different GNSS systems requires a realistic stochastic model for all observations to achieve the best linear unbiased estimation (BLUE) of unknown parameters in multi-GNSS data processing mode. In addition, the correct integer ambiguity resolution (IAR) becomes crucial in shortening the Time-To-Fix (TTF) in RTK, especially in challenging environmental conditions. In general, it is required to estimate various variances for observation types, consider the correlation between different observables, and compensate for the satellite elevation dependence of the observable precision. Quality control of GNSS signals, such as GPS, GLONASS, Galileo, and BeiDou can be performed by processing a zero or short baseline double difference pseudorange and carrier phase observations using the least-squares variance component estimation (LS-VCE). The efficacy of this method is investigated using real multi-GNSS data sets collected by the Trimble NETR9, SEPT POLARX5, and LEICA GR30 receivers. The results show that the standard deviation of observations depends on the system and the observable type in which a particular receiver could have the best performance. We also note that the estimated variances and correlations among different observations are also dependent on the receiver type. It is because the approaches utilized for the recovery techniques differ from one type of receiver to another kind. The reliability of IAR will improve if a realistic stochastic model is applied in single or multi-GNSS data processing. According to the results, for the data sets considered, a realistic stochastic model can increase the computed empirical success rate to 100% in multi-GNSS as well as a single system. As mentioned previously, the realistic precision of the solution can be achieved with a realistic stochastic model. However, using the estimated stochastic model, in fact, leads to better precision and accuracy for the estimated baseline components, up to 39% in multi-GNSS.

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.

scholarly journals Sequential Ambiguity Resolution Method for Poorly-Observed GNSS Data

2021 ◽  
Vol 13 (11) ◽  
pp. 2106
Author(s):  
Haiyang Li ◽  
Guigen Nie ◽  
Shuguang Wu ◽  
Yuefan He
Keyword(s):  
Success Rate ◽  
Ambiguity Resolution ◽  
Satellite System ◽  
Integer Ambiguity ◽  
Double Difference ◽  
Resolution Method ◽  
Substitution Process ◽  
Iterative Correction ◽  
Ambiguity Success Rate ◽  
Gnss Data

Integer ambiguity resolution is required to obtain precise coordinates for the global navigation satellite system (GNSS). Poorly observed data cause unfixed integer ambiguity and reduce the coordinate accuracy. Previous studies mostly used denoise filters and partial ambiguity resolution algorithms to address this problem. This study proposes a sequential ambiguity resolution method that includes a float solution substitution process and a double-difference (DD) iterative correction equation process. The float solution substitution process updates the initial float solution, while the DD iterative correction equation process is used to eliminate the residual biases. The satellite-selection experiment shows that the float solution substitution process is adequate to obtain a more accurate float solution. The iteration-correction experiment shows that the double-difference iterative correction equation process is feasible with an improvement in the ambiguity success rate from 28.4% to 96.2%. The superiority experiment shows significant improvement in the ambiguity success rate from 36.1% to 83.6% and a better baseline difference from about 0.1 m to 0.04 m. It is proved that the proposed sequential ambiguity resolution method can significantly optimize the results for poorly-observed GNSS data.

scholarly journals Empirical Stochastic Model of Multi-GNSS Measurements

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4566
Author(s):  
Dominik Prochniewicz ◽  
Kinga Wezka ◽  
Joanna Kozuchowska
Keyword(s):  
Stochastic Model ◽  
Density Ratio ◽  
Functional Model ◽  
Optimal Solution ◽  
Global Navigation Satellite Systems ◽  
Unknown Parameters ◽  
Short Baseline ◽  
Stochastic Parameters ◽  
Dependent Model ◽  
The Impact

The stochastic model, together with the functional model, form the mathematical model of observation that enables the estimation of the unknown parameters. In Global Navigation Satellite Systems (GNSS), the stochastic model is an especially important element as it affects not only the accuracy of the positioning model solution, but also the reliability of the carrier-phase ambiguity resolution (AR). In this paper, we study in detail the stochastic modeling problem for Multi-GNSS positioning models, for which the standard approach used so far was to adopt stochastic parameters from the Global Positioning System (GPS). The aim of this work is to develop an individual, empirical stochastic model for each signal and each satellite block for GPS, GLONASS, Galileo and BeiDou systems. The realistic stochastic model is created in the form of a fully populated variance-covariance (VC) matrix that takes into account, in addition to the Carrier-to-Noise density Ratio (C/N0)-dependent variance function, also the cross- and time-correlations between the observations. The weekly measurements from a zero-length and very short baseline are utilized to derive stochastic parameters. The impact on the AR and solution accuracy is analyzed for different positioning scenarios using the modified Kalman Filter. Comparing the positioning results obtained for the created model with respect to the results for the standard elevation-dependent model allows to conclude that the individual empirical stochastic model increases the accuracy of positioning solution and the efficiency of AR. The optimal solution is achieved for four-system Multi-GNSS solution using fully populated empirical model individual for satellite blocks, which provides a 2% increase in the effectiveness of the AR (up to 100%), an increase in the number of solutions with errors below 5 mm by 37% and a reduction in the maximum error by 6 mm compared to the Multi-GNSS solution using the elevation-dependent model with neglected measurements correlations.

scholarly journals Improving GNSS Ambiguity Acceptance Test Performance with the Generalized Difference Test Approach

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3018 ◽  
Author(s):  
Lei Wang ◽  
Ruizhi Chen ◽  
Lili Shen ◽  
Yanming Feng ◽  
Yuanjin Pan ◽  
...  
Keyword(s):  
Success Rate ◽  
Failure Rate ◽  
Rapid Determination ◽  
Integer Ambiguity ◽  
Threshold Function ◽  
Acceptance Test ◽  
Data Set ◽  
Fixed Failure Rate ◽  
Gnss Data ◽  
Difference Test

In Global navigation satellite system (GNSS) data processing, integer ambiguity acceptance test is considered as a challenging problem. A number of ambiguity acceptance tests have been proposed from different perspective and then unified into the integer aperture estimation (IA) framework. Among all the IA estimators, the optimal integer aperture (OIA) achieves the highest success rate with the fixed failure rate tolerance. However, the OIA is of less practical appealing due to its high computation complexity. On the other hand, the popular discrimination tests employ only two integer candidates, which are the essential reason for their sub-optimality. In this study, a generalized difference test (GDT) is proposed to exploit the benefit of including three or more integer candidates to improve their performance from theoretical perspective. The simulation results indicate that the third best integer candidates contribute to more than 70% success rate improvement for integer bootstrapping success rate higher than 0.8 case. Therefore, the GDT with three integer candidates (GDT3) achieves a good trade-off between the performance and computation burden. The threshold function is also applied for rapid determination of the fixed failure rate (FF)-threshold for GDT3. The performance improvement of GDT3 is validated with real GNSS data set. The numerical results indicate that GDT3 achieves higher empirical success rate while the empirical failure rate remains comparable. In a 20 km baseline test, the success rate GDT3 increase 7% with almost the same empirical failure rate.

scholarly journals Detection and elimination method for deception jamming based on an antenna array

2018 ◽  
Vol 14 (5) ◽  
pp. 155014771877446 ◽  
Author(s):  
Shuyan Ni ◽  
Jianhua Cui ◽  
Naiping Cheng ◽  
Yurong Liao
Keyword(s):  
Global Positioning System ◽  
Measurement Errors ◽  
Integer Ambiguity ◽  
Double Difference ◽  
Fast Method ◽  
Short Baseline ◽  
Elimination Method ◽  
Medium Length ◽  
Global Positioning ◽  
Jamming Detection

A global positioning system is an important way of locating an aircraft, while deception jamming can affect the positioning accuracy of such navigation. Considering this, a detection and elimination method for deception jamming is proposed based on a specially designed array for the aircraft. The jamming is detected by comparing the double-difference observation of the carrier phases of two different signals to a certain threshold derived according to the measurement errors of the receiver. To estimate the jamming direction with high accuracy, meanwhile considering the feasibility of airborne installation, a novel configurated array combining medium-length baseline with short baseline is designed, and a fast method to solve the integer ambiguity is discussed. After jamming detection, the nulling of the array beam is pointed to the jamming source through the orthogonal vector weighting to suppress jamming. The validity of the method is verified by computer simulations.

scholarly journals Reduction of ZTD outliers through improved GNSS data processing and screening strategies

2018 ◽  
Vol 11 (3) ◽  
pp. 1347-1361 ◽  
Author(s):  
Katarzyna Stepniak ◽  
Olivier Bock ◽  
Pawel Wielgosz
Keyword(s):  
Data Processing ◽  
Satellite System ◽  
Double Difference ◽  
Reference Network ◽  
Tropospheric Delay ◽  
Daily Data ◽  
Data Gaps ◽  
Short Baselines ◽  
Global Navigation Satellite ◽  
Gnss Data

Abstract. Though Global Navigation Satellite System (GNSS) data processing has been significantly improved over the years, it is still commonly observed that zenith tropospheric delay (ZTD) estimates contain many outliers which are detrimental to meteorological and climatological applications. In this paper, we show that ZTD outliers in double-difference processing are mostly caused by sub-daily data gaps at reference stations, which cause disconnections of clusters of stations from the reference network and common mode biases due to the strong correlation between stations in short baselines. They can reach a few centimetres in ZTD and usually coincide with a jump in formal errors. The magnitude and sign of these biases are impossible to predict because they depend on different errors in the observations and on the geometry of the baselines. We elaborate and test a new baseline strategy which solves this problem and significantly reduces the number of outliers compared to the standard strategy commonly used for positioning (e.g. determination of national reference frame) in which the pre-defined network is composed of a skeleton of reference stations to which secondary stations are connected in a star-like structure. The new strategy is also shown to perform better than the widely used strategy maximizing the number of observations available in many GNSS programs. The reason is that observations are maximized before processing, whereas the final number of used observations can be dramatically lower because of data rejection (screening) during the processing. The study relies on the analysis of 1 year of GPS (Global Positioning System) data from a regional network of 136 GNSS stations processed using Bernese GNSS Software v.5.2. A post-processing screening procedure is also proposed to detect and remove a few outliers which may still remain due to short data gaps. It is based on a combination of range checks and outlier checks of ZTD and formal errors. The accuracy of the final screened GPS ZTD estimates is assessed by comparison to ERA-Interim reanalysis.

scholarly journals Kinematic GNSS positioning results compared against Agisoft Metashape and Pix4dmapper results produced in the San Joaquin experimental range in Fresno County, California

2021 ◽  
Vol 11 (1) ◽  
pp. 48-57
Author(s):  
M. Berber ◽  
R. Munjy ◽  
J. Lopez
Keyword(s):  
Data Processing ◽  
Global Navigation Satellite Systems ◽  
Kinematic Data ◽  
Fresno County ◽  
Satellite Systems ◽  
Data Processing Software ◽  
Recent Developments ◽  
Processing Modes ◽  
Global Navigation Satellite ◽  
Gnss Data

Abstract RTKLIB which is an open source Global Navigation Satellite Systems (GNSS) software has gained rapid acceptance among Surveying professionals thanks to recent developments in UAS (Unmanned Aerial System) technology. RTKLIB enables standard and precise point positioning (PPP) in real-time and post-processing modes to be performed. As such, UAS users utilize this software to analyze GNSS data collected by GNSS systems on UAS. By being versatile and free, RTKLIB is commonly used by many; however, it is not the only freely available GNSS software. There are also freely available online GNSS data processing software running on servers. These online GNSS data processing services provide data processing in static, kinematic and rapid static modes. Because UAS collect data in kinematic mode, in this study, kinematic data processing by aforementioned software (CSRS-PPP, GAPS and APPS) is analyzed. The results coming from these software are compared against the results produced by photogrammetric software (Agisoft Metashape and Pix4Dmapper). The aim of this practical project is to produce generalizable knowledge about the performance of these software. It is found out that RTKLIB and CSRS-PPP achieved cm-level precision. Yet, GAPS and APPS achieved dm-level precision both for horizontal and vertical coordinates. This study demonstrates the precision and accuracy expected from these software if they are used for kinematic GNSS data processing.

scholarly journals Reduction of ZTD outliers through improved GNSS data processing and screening strategies

2017 ◽  
Author(s):  
Katarzyna Stepniak ◽  
Olivier Bock ◽  
Pawel Wielgosz
Keyword(s):  
Data Processing ◽  
Satellite System ◽  
Double Difference ◽  
Reference Network ◽  
Tropospheric Delay ◽  
Daily Data ◽  
Data Gaps ◽  
Short Baselines ◽  
Global Navigation Satellite ◽  
Gnss Data

Abstract. Though Global Navigation Satellite System (GNSS) data processing has been significantly improved over years it is still commonly observed that Zenith Tropospheric Delay (ZTD) estimates contain many outliers which are detrimental to meteorological and climatological applications. In this paper, we show that ZTD outliers in double difference processing are most of the time caused by sub-daily data gaps at reference stations which cause disconnections of clusters of stations from the reference network and common–mode biases due to the strong correlation between stations in short baselines. They can reach a few centimetres in ZTD and coincide usually with a jump in formal errors. The magnitude and sign of these biases are impossible to predict because they depend on different errors in the observations and on the geometry of the baselines. We elaborate and test a new baseline strategy which solves this problem and significantly reduces the number of outliers compared to the standard strategy commonly used for positioning (e.g. determination of national reference frame) in which the pre-defined network is composed of a skeleton of reference stations to which secondary stations are connected in a star-like structure. The new strategy is also shown to perform better than the widely-used strategy maximising the number of observations which available in many GNSS software. The reason is that observations are maximised before processing whereas the final number of used observations can be dramatically lower because of data rejection (screening) during the processing. The study relies on the analysis of one year of GPS (Global Positioning System) data from a regional network of 136 GNSS stations processed using Bernese GNSS Software v.5.2. A post-processing screening procedure is also proposed to detect and remove a few outliers which may still remain due to short data gaps. It is based on a combination of range checks and outlier checks of ZTD and formal errors. The accuracy of the final screened GPS ZTD estimates is assessed by comparison to ERA-Interim reanalysis.

scholarly journals High-Accuracy Attitude Determination Using Single-Difference Observables Based on Multi-Antenna GNSS Receiver with a Common Clock

2021 ◽  
Vol 13 (19) ◽  
pp. 3977
Author(s):  
Chenglong Zhang ◽  
Danan Dong ◽  
Wen Chen ◽  
Miaomiao Cai ◽  
Yu Peng ◽  
...  
Keyword(s):  
Pitch Angle ◽  
Attitude Determination ◽  
Clock Synchronization ◽  
Integer Ambiguity ◽  
Double Difference ◽  
Fiber Optic Gyroscope ◽  
Short Baseline ◽  
Practical Applications ◽  
Gnss Receiver ◽  
Single Difference

A global navigation satellite system (GNSS) receiver with multi-antenna using clock synchronization technology is a powerful piece of equipment for precise attitude determination and reducing costs. The single-difference (SD) can eliminate both the satellites and receiver clock errors with the common clock between antennas, which benefits the GNSS short-baseline attitude determination due to its lower noise, higher redundancy and stronger function model strength. However, the existence of uncalibrated phase delay (UPD) makes it difficult to obtain fixed SD attitude solutions. Therefore, the key problem for the fixed SD attitude solutions is to separate the SD UPD and fix the SD ambiguities into integers between antennas. This article introduces the one-step ambiguity substitution approach to separate the SD UPD, through which we merge the SD UPD parameter with the SD ambiguity of the reference satellite ambiguity as the new SD UPD parameter. Reconstructing the other SD ambiguities, the rank deficiency can be remedied by nature, and the new SD ambiguities can have a natural integer feature. Finally, the fixed SD baseline and attitude solutions are obtained by combining the ambiguity substitution approach with integer ambiguity resolution (IAR). To verify the effect of the ambiguity substitution approach and the advantages of the SD observables with a common clock in practical applications, we conducted static, kinematic, and vehicle experiments. In static experiments, the root mean squared errors (RMSEs) of the yaw and pitch angles obtained by the SD observables with a common clock were improved by approximately 80% and 93%, respectively, compared to double-difference (DD) observables with a common clock in multi-day attitude solutions. The kinematic results show that the dispersion of the SD-Fix in the pitch angle is two times less that of the DD-Fix, and the standard deviations (STDs) of the pitch angle for SD-Fix can reach 0.02°. Based on the feasibility, five bridges with low pitch angles in the vehicle experiment environment, which the DD observables cannot detect, were detected by the SD observables with a common clock. The attitude angles obtained by the SD observables were also consistent with the fiber optic gyroscope (FOG) inertial navigation system (INS). This research on the SD observables with a common clock provides higher accuracy.

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.

Sign in / Sign up

Export Citation Format

Share Document