GNSS Positioning Research Articles

A Modelling Study by Factorial Design on GNSS Positioning

Although researchers have widely studied the analysis and modelling of error sources on Global Navigation Satellite Systems positioning, some of these errors have not been eliminated significantly and only some of the Global Navigation Satellite System’s data are modelled. The present work was undertaken to determine the effect of different variables, namely: season, the number of visible satellites, and dilution of precision on the efficiency of horizontal and vertical CORS (Continuously Operating Reference Stations) positioning. For this aim, the CORS data was collected at 14 different test points during 600 epochs with 1-second intervals. Factorial designs supply an efficient solution to understand the impact of several factors on a response variable. A full factorial design with three factors at two levels was applied for these purposes. According to the results of the full factorial design, all factors significantly affected the response variable. Also, the interaction effects of factors were analysed on the CORS horizontal and vertical positioning. The regression equations were obtained for all situations.

Introducing Metrics to Analyse the Performance of Automatic Section Control for Agricultural Machines

In this paper, three metrics are proposed and explored for the purpose of analysing and quantifying the performance of any system that uses an ISO 11783 task controller (TC) to automatically control the on/off state of its sections based on GNSS positioning. The issues that can affect TC performance are presented, and equations are shown to calculate the areas of product overlap and gaps. A theoretical example TC is presented and analysed against the proposed metrics to demonstrate the value of the metrics in detailing the performance of a TC in the real case. The causes of errors in real-world situations are discussed and their impacts on the metrics are considered.

Orthometric, normal and geoid heights in the context of the Brazilian altimetric network

The extensive use of GNSS positioning, combined with the importance of precise geoid heights for transformation between geodetic and orthometric heights, brings up the discussion of the influence of data uncertainties and the use of variable density values on these estimates. In this sense, we analyze the influence of the topographic masses density distribution and the data uncertainty on the computation of orthometric and geoid heights in stations of the High Precision Altimetric Network of Brazil, considering the Helmert and Mader methods. For this, we use 569 stations whose values of geodetic and normal heights, gravity, and geopotential numbers are known. The results indicate that orthometric heights are more sensitive to density values and to greater heights than to the Helmert and Mader methods applied. Also, we verify that the normal and orthometric heights present significant differences for the analyzed stations, considering the high correlation between the heights, which provide small values of uncertainty. However, our analyses show that the use of the Mader method, along with variable density values, provides either more rigorous or more reliable results.

Performance of Different SLAM Algorithms for Indoor and Outdoor Mapping Applications

Indoor and outdoor mapping studies can be completed relatively quickly, depending on the developments in Mobile Mapping Systems. Especially in indoor environments where high accuracy GNSS positions cannot be used, mapping studies can be carried out with SLAM algorithms. Although there are many different SLAM algorithms in the literature, each can produce results with different accuracy according to the mapped environment. In this study, 3D maps were produced with LOAM, A-LOAM, and HDL Graph SLAM algorithms in different environments such as long corridors, staircases, and outdoor environments, and the accuracies of the maps produced with different algorithms were compared. For this purpose, a mobile mapping platform using Velodyne VLP-16 LIDAR sensor was developed, and the odometer drift, which causes loss of accuracy in the data collected, was minimized by loop closure and plane detection methods. As a result of the tests, it was determined that the results of the LOAM algorithm were not as accurate as those of the A-LOAM and HDL Graph SLAM algorithms. Both indoor and outdoor environments and the A-LOAM results’ accuracy were two times better than HDL Graph SLAM results.

General Geometric Model of GNSS Position Time Series for Crustal Deformation Studies – A Case Study of CORS Stations in Vietnam

In processing of position time series of crustal deformation monitoring stations by continuousGNSS station, it is very important to determine the motion model to accurately determine the displacementvelocity and other movements in the time series. This paper proposes (1) the general geometric model foranalyzing GNSS position time series, including common phenomena such as linear trend, seasonal term,jumps, and post-seismic deformation; and (2) the approach for directly estimating time decay ofpostseismic deformations from GNSS position time series, which normally is determined based on seismicmodels or the physical process seismicity, etc. This model and approach are tested by synthetic positiontime series, of which the calculation results show that the estimated parameters are equal to the givenparameters. In addition they were also used to process the real data which is GNSS position time series of4 CORS stations in Vietnam, then the estimated velocity of these stations: DANA (n, e, u = -9.5, 31.5, 1.5mm/year), HCMC (n, e, u = -9.5, 26.2, 1.9 mm/year), NADI (n, e, u = -10.6, 31.5, -13.4 mm/year), andNAVI (n, e, u = -13.9, 32.8, -1.1 mm/year) is similar to previous studies.

Analysis of GNSS Displacements in Europe and Their Comparison with Hydrological Loading Models

Thanks to the increasing number of permanent GNSS stations in Europe and their long records, we computed position solutions for more than 1000 stations over the last two decades using the REPRO3 orbit and clock products from the IGS CNES-CLS (GRGS) Analysis Center. The velocities, which are mainly due to tectonics and glacial isostatic adjustment (GIA), and the annual solar cycle have been estimated using weighted least squares. The interannual variations have been accounted for in the stochastic model or in the deterministic model. We demonstrated that the velocity and annual cycle, in addition to their uncertainties, depend on the estimation method we used and that the estimation of GPS draconitic oscillations minimises biases in the estimation of annual solar cycle displacements. The annual solar cycle extracted from GPS has been compared with that from loading estimates of several hydrological models. If the annual amplitudes between GPS and hydrological models match, the phases of the loading models were typically in advance of about 1 month compared to GPS. Predictions of displacements modelled from GRACE observations did not show this phase shift. We also found important discrepancies at the interannual frequency band between GNSS, loading estimates derived from GRACE, and hydrological models using principal component analysis (PCA) decomposition. These discrepancies revealed that GNSS position variations in the interannual band cannot be systematically interpreted as a geophysical signal and should instead be interpreted in terms of autocorrelated noise.

Convergence of daily mean coordinates of precise positioning methods

As part of the research of modern movements of the Earth’s crust, an analysis of 7 high-precision methods for calculating GNSS positions was carried out for the convergence of their daily mean coordinates. Based on Euclidean distances, regular and maximal discrepancies between coordinates of different methods are given. According to the coordinates in the ITRF, 5 methods are stood out with regular coordinate discrepancies <1 mm, and individual maximum discrepancies up to 30 mm. The other two methods have regular discrepancies in coordinates up to 2 cm, and the maximum differences reach 1 m. For a group of stations global coordinates transformation into a local reference frame leads to the effect of coordinate stabilization and increases their relative precision in the time series. As a result of such procedure, the level of maximum coordinate discrepancies between the methods decreased to 46%. Moreover, one of the methods of calculating coordinates has improved its convergence with the other methods by 80%. Based on the Euclidean distance method, the quality of the raw data for each station was evaluated. Thus, there is a group of 8 stations, for which the convergence of coordinates in different methods are approximately at the same level, and 2-3 times better than for the other 2 stations.

Comparison Analysis on the Accuracy of Galileo PPP Using Different Frequency Combinations in Europe

The Galileo constellations are characterized by transmitting GNSS signals on multi-frequencies, which can benefit the robustness and accuracy of the solutions. However, the dual-frequency E1/E5a combinations are generally used for precise point positioning (PPP). In this paper, the performance of Galileo static and kinematic PPP using different dual- and multi-frequency combinations are assessed using observations from the European region. Overall, the accuracy of daily PPP achieved by the dual-frequency GPS, Galileo, and BDS is better than 5 mm in the horizontal direction and better than 10 mm in the vertical direction. Though the number of observed Galileo satellites is less than GPS, the horizontal accuracy can reach 1.6 mm/2.3 mm/5.7 mm on North/East/Up component, which is improved by 59.0% and 12.3% compared to the GPS in the north and up direction. Then, the accuracy of Galileo static PPP is analyzed using different dual- and multi-frequency combinations. Results indicate that the Galileo E1/E5b PPP can degrade the accuracy due to the inter-frequency clock biases between the E1/E5a and E1/E5b combinations. Best accuracy can be achieved for the triple- and four-frequency PPP, which is 4.8 mm in the up direction. The hourly accuracy for the static PPP can reach 5.6 mm/9.2 mm/12.6 mm in the north/east/up direction using the GPS/Galileo/GLONASS/BDS combinations. Finally, a positioning convergence ratio (PCR) indicator, which represents the accuracy of PPP over a period, is used to analyze the convergence time of kinematic PPP. Results indicated that the multi-frequency Galileo observations contribute minorly to the convergence of kinematic PPP. However, Galileo shows the best convergence performance for the single GNSS positioning, and the GPS/Galileo combined PPP achieved the best performance for the PPP using different GNSS combinations.

High-Accuracy GNSS Positioning of Ocean Vessels for Sea Wave Monitoring

Kim, M. and Bae, T.-S., 2021. High-accuracy GNSS positioning of ocean vessels for sea wave monitoring. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 415–419. Coconut Creek (Florida), ISSN 0749-0208. This study aims to develop a high-precision strategy for the positioning of marine vessels to monitor sea waves. Thus, the total electron content (TEC) in the ionosphere will be accurately corrected in the positioning process. We analyzed various aspects of ionospheric delay using the Global Ionosphere Map (GIM). The results indicated that the ionosphere was affected by the frequencies and long-term changes of the TEC. It is critical to synchronize the correction information and GNSS observation data on ocean vessels. We developed a methodology for the time synchronization of the GIM, specifically for the ocean, on which only a small number of continuously operating reference station (CORS) networks are available. The generated ionosphere model was compared to the GIM with a maximum of 1.6 TEC, which should be verified for a longer period of time.

A New Approach for the Development of Grid Models Calculating Tropospheric Key Parameters over China

Pressure, water vapor pressure, temperature, and weighted mean temperature (Tm) are tropospheric parameters that play an important role in high-precision global navigation satellite system navigation (GNSS). As accurate tropospheric parameters are obligatory in GNSS navigation and GNSS water vapor detection, high-precision modeling of tropospheric parameters has gained widespread attention in recent years. A new approach is introduced to develop an empirical tropospheric delay model named the China Tropospheric (CTrop) model, providing meteorological parameters based on the sliding window algorithm. The radiosonde data in 2017 are treated as reference values to validate the performance of the CTrop model, which is compared to the canonical Global Pressure and Temperature 3 (GPT3) model. The accuracy of the CTrop model in regards to pressure, water vapor pressure, temperature, and weighted mean temperature are 5.51 hPa, 2.60 hPa, 3.09 K, and 3.35 K, respectively, achieving an improvement of 6%, 9%, 10%, and 13%, respectively, when compared to the GPT3 model. Moreover, three different resolutions of the CTrop model based on the sliding window algorithm are also developed to reduce the amount of gridded data provided to the users, as well as to speed up the troposphere delay computation process, for which users can access model parameters of different resolutions for their requirements. With better accuracy of estimating the tropospheric parameters than that of the GPT3 model, the CTrop model is recommended to improve the performance of GNSS positioning and navigation.

Low-cost positioning performance using remotely sensed ionosphere

Low-Cost Positioning [Single Frequency Receivers (SFR)] using Global Positioning Systems (GPS) can become a precise alternative to Dual Frequency Receivers (DFRs) in different applications. Ionospheric delay is one of the significant provenances of errors in GPS navigation and positioning. These blunders in both Phase range and pseudo range can differ according to the receiver location, solar cycle, time, and geomagnetic activity.Some ground receivers over Egypt and Europe were regarded in This publication to examine various ionosphere correction products' capability. Data from IGS stations spanning various latitudes and solar activity times (high, medium, or small) are taken into account. The findings demonstrate that the sub-meter level's precision is obtainable using single-frequency data using suitable mitigation approaches for ionospheric impacts.The implications for GNSS positioning (especially on horizontal precision) of ionospheric corrections have been studied. The findings demonstrate that all ionosphere corrections clearly enhance the accuracy of the vertical positions where the absolute vertical error is about 30 cm, 32.3 cm, and 57.2 cm for LIMs (Local Ionosphere Maps), GIMs (Global Ionosphere Maps), and BKP (Broadcasted Klobuchar Parameter). However, the horizontal enhancement is lower than the vertical, and even worse, the horizontal error can be increased with ionosphere correction. The horizontal error ranges from 2.7 to 51.8 cm by using LIMs, while ranges from 4.5 to 47.2 cm by using GIMs but the maximum horizontal error obtained by applying BKP, which ranges from 20.7 to 100.2 cm. In comparison, the north bias plays a vital role in reducing horizontal precision. If north bias were not resolved correctly with ionosphere corrections, the horizontal positioning efficiency would deteriorate.The significant efficiency of mid-latitude Egyptian ionosphere correction (estimated by LIMs) in stormy and quiet geomagnetic environments rather than GIMs and BKP, 3D RMS error improved by 16 %, and GIMs up 63 %. Furthermore, in low solar activity, 3D RMS error improved 6% compared to GIMs and 87% compared to BKP.

COMBINING TERRESTRIAL SCANNED DATASETS WITH UAV POINT CLOUDS FOR MINING OPERATIONS

Abstract. Surveyors of open cut mining operations employ multiple data acquisition techniques such as the use of Unmanned Aerial Vehicles (UAV), Terrestrial Laser Scanning (TLS) and GNSS positioning for creating 3D surface models. Surveyors, mine planners and geologists are increasingly combining point cloud datasets to achieve more detailed surface models for the use of material reconciliation and volume calculations. Terrestrial Laser Scanning and UAV photogrammetry have enabled large, accurate and time effective data collection and increased computing capacity enables geospatial professionals to create 3D virtual surfaces, through merging UAV point clouds and TLS data combing with GNSS positioning. This research paper investigates the effects of combining data sets for creating 3D surface models from independent spatial data collection methods such as UAV, TLS and GNSS and assess their accuracy for the purpose of volume calculations in mining operation. 3D surface models provide important information for mining operations, planning of resources, material volumes calculation and financial calculations. A case study of two rehabilitation mine sites in Northern Victoria, Australia was selected for this study. Field data were collected using Terrestrial Laser Scanner and UAV. After each dataset was processed and filtered, the data were merged to create surface models. The accuracy of the combined model was assessed comparing height (Z) values using a fishnet point grid of the surfaces. Volumes between surfaces were calculated, and a cost applied to the results based on the current bulk cubic meter (BCM) haulage rates. The outputs from this study will provide scientific contributions to civil and mining industries where the computation of stockpile values is required.

Robust GNSS Shadow Matching for Smartphones in Urban Canyons

GNSS is being widely used in different applications in navigation. However, GNSS positioning is greatly challenged by notorious multipath effects and non-line-of-sight (NLOS) receptions. The signal blockage and reflection by buildings cause these effects. In other words, the more urbanized the city is, the more challenge on the GNSS positioning. The conventional multipath mitigation approaches, such as the sophisticated design of GNSS receiver correlator, can efficiently mitigate the most of multipath effects. However, it has less capability against NLOS reception, potentially leading to several tens of positioning errors. Therefore, the 3D mapping aided (3DMA) GNSS positioning is introduced to exclude or even use the NLOS signal. Shadow matching is to make use of the similarity between building geometry and satellite visibility to improve the positioning performance. This paper introduces a machine learning intelligent classifier with features to distinguish LOS and NLOS. With the NLOS reception classification, the positioning accuracy of shadow matching can be increased. In addition, this paper develops several indicators to label the unreliable solution of shadow matching. These indicators are to examine the complexity of the surrounding environment, which is the key factor relating to the proposed shadow matching performance. Several designed experiments were done in Hong Kong to evaluate the proposed method. With the intelligent classifier, the average positioning accuracy is about 15m and 6m on 2D and the across-street direction, respectively. Simultaneously, the reliability evaluation rules can exclude unreliable epoch and improve the positioning results, especially on smartphone data.

Performance of the non-iterative ToA-based positioning algorithms in complex indoor environments

The Gauss-Newton algorithm has been widely used in GNSS positioning and indoor positioning applications, but it requires an initial guess. An unfavorable initial guess may cause the iteration divergence. This issue is particularly important in indoor positioning scenarios but has not attracted enough attention. The non-iterative closed-form algorithms are suitable to provide the initial guess since they are divergence-free but sub-optimal. This study systematically evaluated performance of four representative non-iterative closed-form algorithms, namely the differenced squared range (DSR) algorithm, the Bancroft algorithm, and constrained virtual parameter (CVP) algorithm in terms of positioning precision, robustness, and computation efficiency. The performance of these algorithms is evaluated with both simulative data and real data. The results indicate that the CVP algorithm achieves 0.2–0.6 m accuracy in the static scenarios and about 2 m accuracy in the kinematic scenario, which outperforms the Gauss-Newton algorithm and the other two non-iterative approaches. The Gauss-Newton approach also achieves promising results in the LOS scenario, but it is more vulnerable to the NLOS observations. The DSR algorithm and the Bancroft algorithms are sub-optimal, robust to NLOS biases, but their performance in real data test depends on the test scenario. The CVP algorithm is free of divergence issue, robust to NLOS bias, and computationally efficient and achieves the best positioning accuracy in all four algorithms, thus should be recommended in highly non-linear localization estimation scenarios, such as the indoor positioning applications.

The Research Activities of the Main Astronomical Observatory of the National Academy of Sciences of Ukraine on the Use of GNSS Technology

The current state of the research activities of the Main Astronomical Observatory of the National Academy of Sciences of Ukraine (MAO NASU) on the use of GNSS technology is presented. Today, MAO operates a permanent GNSS network consisting of five stations (two stations are temporarily inactive). All stations are included in EPN and the EPOS network, GLSV, KHAR, and UZHL stations are also integrated to the IGS network. MAO Operational Centre also provides automatic data transfer from 12 stations installed by other Ukrainian organizations included in the international networks. Data from approximately 300 Ukrainian permanent GNSS stations are stored in the MAO Local Data Centre. The MAO Local Analysis Centre uses Bernese GNSS Software for different types of data processing of GNSS observations. Rapid processing is performed on a daily basis for monitoring the stability of the permanent stations from some Ukrainian RTK networks. All available observations data from the Ukrainian stations for the period from December 7, 1997, to January 28, 2017, were processed according EPN standards during the MAO’s second reprocessing campaign and regular processing. As a result, the coordinates in the IGb08 reference frame and tropospheric zenith delays for 233 permanent stations (202 of them are the Ukrainian stations), as well as the velocities for the 128 stations that have observation period more than 3 years, were estimated. The creation and development of local GNSS networks, as well as the long-term filling of databases with high-precision coordinate solutions and estimates of the displacement velocities of GNSS stations, made possible to conduct geodynamic studies at the local level. The strain ellipses and rotation were found based on estimated coordinates and velocities of the GNSS stations. In 2016–2019, Kharkiv National University of Radio Electronics, in cooperation with MAO NASU, performed a number of studies on high-precision GNSS positioning and navigation. New implementations of modern methods and algorithms for the PPP positioning were created and experimentally tested. The errors of the daily floating PPP solutions were 5…8 mm (with a probability of P ≈ 95%) for static mode and 5…8 cm (P ≈ 68%) for kinematic mode. The decimeter/centimeter error of determining the coordinates of current satellites with low Earth orbits (LEO) in the implementation of kinematic floating and fixed PPP solutions was proven. The development of a high-accuracy multiposition phase system of trajectory measurements for field tests of high dynamic aircrafts (HDA) were proposed. The estimated values of the root-mean-square error (RMSE) in determining the HDA motion variables were in the range from 0.05 to 0.40 m for coordinates and from 0.5 to 1.6 cm/s for the velocity vector components.

An Investigation on the Performance of Soft Computing Techniques for Point Displacement Modeling for Suspension Bridge Using GNSS Technique

Bridges are playing a major role in the socio-economic development of any country over the world. Suspension bridges are one of the most sensitive structures to various external influences and loads. Therefore, the need for structural monitoring system, maintenance and deformation prediction for these types of structures is important and vital. Time of observations for the purpose of structural deformation can vary from a few hours, days to several months or even years. This paper investigates the performance of several soft computing techniques for point displacement modeling using GNSS technique during the process of monitoring the structural deformation of suspension highway bridge, taking into consideration the effect of wind, temperature, humidity and traffic loads during the operational and short-term measurements. Due to the availability of a large amount of positions data generated from GNSS data positions for monitoring the deformation of such structure, artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) should be chosen. One of the main objectives of this paper is to investigate the optimum predictive soft computing model for processing GNSS positions and points displacement prediction. Several mathematical models and two cases of data amount (66.67% and 50% of all available data) for dynamic and kinematic state are applied and compared for prediction of suspension bridge displacement with confidence interval with a probability ρ = 0.95, Δ = ± 2σ. The resulting point displacement values by applying ANNs and ANFIS, which used a confidence interval with a probability of ρ = 0.95, Δ = ± 2σ when using 66.67% of all data, are more accurate and reliable than any other applied methods, and therefore, ANNs and ANFIS can provide a significant improvement of understanding and predicting the structure deformation values where conventional mathematical modeling techniques were not as accurate or capable especially in dynamic prediction of displacements.

Application of Phase-Only Correlation to Travel-Time Determination in GNSS-Acoustic Positioning

The GNSS-acoustic technique is a geodetic method for oceanic areas that combines GNSS positioning of a sea-surface platform and acoustic ranging of seafloor stations. Its positioning accuracy is typically a few and several centimeters for the horizontal and vertical positions, respectively. For further accuracy enhancement, we examined the errors in travel time, the most fundamental data in acoustic ranging. The reference signal used in our observations is a series of sinusoidal waves modulated by binary phase-shift keying with a maximal length sequence whose auto-correlation has a clear main peak at zero lag. However, cross-correlation between the actual returned signal and reference signal is often accompanied by many large sidelobes and looks very different from the synthetic auto-correlation. As a practical measure, we have chosen empirically one peak among several comparable peaks in the cross-correlation, though that is likely to lead to systematic errors in travel time. In this study, we revealed that a variety of cross-correlation waveform primarily depends on the incident angle of acoustic paths and that sidelobes were significantly reduced by substituting phase-only correlation (POC) for conventional cross-correlation. We therefore developed a template-matching technique using POC for the peak detection. POC templates were prepared by stacking actual POCs with certain ranges of the incident angle for each campaign. In the application of this method to actual data, we achieved successful results of our numerous campaign data to date. We consider that POC is advantageous in identifying the main peak uniquely and performing template matching more robustly, because POC enhances short-period components and thus highlights the timing of phase changes further than conventional cross-correlation.

Precision and Characteristics Analysis of Precise Satellite Clock Bias Data of BDS

High-precision satellite clock bias (SCB) data is a critical product for satellite navigation systems to realize accurate navigation, positioning and timing. Unlike other satellite navigation systems, the precise SCB data for the BeiDou Navigation Satellite System (BDS) are mainly determined by two methods, the Two-Way Time Transfer (TWTT) method and the Orbit Determination and Time Synchronization (ODTS) method. Awareness of the data variations obtained from different methods can be used to improve clock modeling performance, and be beneficial to higher-rate GNSS positioning and for predictions in real-time applications. We describe a comprehensive method to analyze the systematic and random characteristics of BDS SCB data obtained from TWTT and ODTS and discuss possible causes of observed variations. Some new conclusions are drawn: the data continuity of TWTT is highly related to satellite orbit types; affected by orbit error and other factors, the fitting residuals (RMS) of ODTS is 0.2 ns worse than that of TWTT on average, while the fitting precision of TWTT is 0.49 ns. There are up to 8ns periodic fluctuations in the mutual agreement between TWTT and ODTS data. The stability result shows a remarkable effect of flicker phase modulation (FLPM) noise can be seen in the period of 300-1000 s in TWTT data. All the BDS satellites display more complex, nonpower law behavior due to the effects of periodic clock variations.

A Vector Ionospheric Delay Correction Method for GNSS Positioning and Navigation Wide Area Augmentation Service

A new ionospheric delay correction method is proposed to improve the ionospheric correction accuracy of single frequency GNSS users. In the new method, the ionospheric grid point information is expanded from a single scalar vertical correction parameter to a vector of triple elements (the triple): vertical correction parameter, north correction parameter and east correction parameter. The new parameters are used to describe the variation of ionospheric delay correction caused by satellite azimuth. Using the observation data of the ground monitoring stations to fit the triple, and then broadcast the triple to the user. GNSS single frequency users can use the triple data to correct their own ionospheric delay. The testing results show that the correction error of the method is around 0.3 m lower than that of the scalar method.

Enhancing BDS-3 precise time transfer with DCB modelling

This article is the first report of BDS-3 differential code bias (DCB) correction models. Satellite differential code biases (SDCBs) were regarded as a source of error; if there was no correction, the quality of the GNSS Position & Navigation & Timing service deteriorated. As a newly built global system, the BDS-3 satellite broadcasted B1I, B3I, B1C and B2a signals. To fully exploit all the BDS-3 signals, DCB correction models related to multiple Dual-Frequency (DF) Ionosphere-Free (IF) combinations were developed for BDS-3 application. Two prevailing global navigation satellite system positioning technologies, namely, standard point positioning (SPP) and precise point positioning (PPP), were utilized to validate the efficacy of the DCB parameters provided by the Multi-GNSS Experiment (MGEX). Our numerical analyses clarified how the DCB model performed when it was applied to positioning and time transfer events under the B1C&B3I, B1I&B2a, B1C&B2a cases. With the use of DCB correction in three combinations, the positioning accuracy and frequency stability were significantly improved. The E, N and U position accuracies of the ondcb scheme compared to those of the offdcb scheme were enhanced in the range of 39.51–86.24%, 35.44–78.64% and 41.84–78.64%, respectively. In particular, we observed that the long-term stability of the time link was obviously better than the short-term stability. The stability percentages were improved by at least 3%, and some were improved by up to 66.5%. The frequency stability obtained by B1I&B3I is equivalent to that obtained by B1C&B3I and B1I&B2a. Finally, all the statistics indicate that the B1C&B2a combination recommended as the optimal option is applicable to time transfer communities. The result agrees with our expectation that the appropriate modelling of DCB is vital, which allows for more precise positioning and a stable time link.