Precise Global Positioning System Research Articles

Advancing container port traffic simulation: A data-driven machine learning approach in sparse data environments

Efficient truck dispatching strategies are paramount in container terminal operations. The quality of these strategies heavily relies on accurate and expedient simulations, which provide a crucial platform for training and evaluating dispatching algorithms. In this study, we introduce data-driven machine learning methods to enhance container port truck dispatching simulation accuracy. These methods effectively surrogate the intersections within the simulation, thereby increasing the accuracy of simulated outcomes without imposing significant computational overhead in sparse data environments. We incorporate three data-driven learning methods: genetic programming (GP), reinforcement learning (RL), and a GP and RL hybrid heuristic (GPRL-H) approach. The GPRL-H method proved the most efficacious through a detailed comparative study, striking an effective balance between simulation accuracy and computational efficiency. It reduced the error rate of simulation from approximately 35% to about 7%, while also halving the simulation time compared to the RL-based method. Our proposed method also does not rely on precise Global Positioning System (GPS) data to simulate truck operations within a port accurately. Demonstrating robustness and adaptability, this approach holds promise for extending beyond port operations to improve the simulation accuracy of vehicle operations in various scenarios characterized by sparse data.

GPS technology as a tool to aid pasture management on dairy farms

This research determined the accuracy and precision of Global Positioning System (GPS) enabled devices as a potential tool to automate the recording of onfarm grazing events, which can be used to indicate productivity of paddocks (with number of grazings per year), or, when combined with other farm data, estimate nergy harvested. Static tests were initially conducted to determine the devices’ accuracy (location error) and precision (Circular Error Probability; CEP). Based on 11 Agtech and 22 mOOvement devices tested, the mean location error was 5.4 m and 34.2 m, respectively. The 95% CEP was 13.9 m and 77.6 m, respectively. In the subsequent on-farm study, 11 cows in a 400- cow milking herd were fitted with an Agtech and mOOvement ear tag and two with digitanimal collars. Data were analysed for the AM and PM grazing periods for four days. The digitanimal collars recorded 62.3% of total observations in the correct paddock, instead of adjacent paddocks or races, compared with 52.5% for the Agtech devices and 45.2% for the mOOvement ear tags. These results suggested that GPS technology isfeasible for the automated recording of grazing events. However, a longer-term study is required to demonstrate the value this technology could have for farmers.

A Novel CSINR Technique for Accurate and Precise GPS Communication by Geographical Centric Self-learning Nodes

Since its introduction, the Global Positioning System (GPS) is finding many countless, useful, and emergency applications, focused mainly on track. As the technology is advancing day by day and the best feature of GPS, which does not, relies on mobile signal to work, making it a feasible feature to incorporate into other devices as functionalities. By adopting GPS to a system, accurate mapping and geographical labeling can be obtained. GPS works better with the coordination of nodes and requires centralized monitoring and a reporting system. As it is a known fact that a demerit follows merit anywhere else, In GPS also, the major attention is required to make the nodes to success in mapping the intermediate space between agent node used for reporting and the remaining nodes of a cluster, where satellite and node coordination can be possible integer ambiguity technique. Many researchers have proposed solutions to the aforementioned problem; unfortunately still today the proposed methods are weaker in achieving lesser time delay of Total Electron Content (TEC). The proposed Centric Self-Learning Interconnected Nodes Reading (CSINR) technique is novel in terms addressing the intermediate nodes failing to label the inter-connected object spaces between reporting agents and nodes using integer ambiguity technique for node co-ordination and using a dedicated GPS prediction-based clock system, which predicts precise and accurate mapping between interconnected nodes. Based on the information shared between among the network managers a separate pseudo-connected network will be formed and further this network will be considered an interconnected nodes network. From the information calculated from temporal factors and clock offset the separate pseudo network is extracted by using the proposed CSINR technique. Add-on self-improvement is introduced to the proposed method by a self--learning feature to an individual join extract the principal rate of partisan neighbouring join to sustain accuracy in order consistent basis. An evaluation ratio of 97.43%, sensitivity of node occurrence is resulted as 92.78% and accuracy of 97.43% and 97.12% is achieved among a cluster of 32and 64 nodes respectively.

On the Establishment of a Precise GPS Network in Khartoum State

The use of the Global Positioning System (GPS) as a fast and efficient alternative in the geodetic network measurements has become a common practice worldwide. The advantages of using the GPS technique compared to the traditional surveying methods are based on accuracy, time and cost. In this study, the static-mode of GPS measurement technique has been utilized to establish a precise geodetic network in Khartoum State. The network was referenced to a single control station that is related to the International Terrestrial Reference Frame (ITRF 2005). A number of six points have been constructed and observed around Khartoum State. In particular, seven observation sessions were conducted that gave an over determined system. The least-squares method was used in the adjustment of the GPS network. Two methods were utilized for the adjustment, namely, the parametric and the condition equation methods. The most probable values of the coordinates of the newly-established points were computed from both methods and they were found to be identical. The average standard deviation of the X, Y, and Z coordinates are ±1.36 cm, ±1.12 cm, & ±0.69 cm respectively.

A precise GSM and GPS integrated fire alarm system

This paper presents the idea of a fire-alarm system that is based on Global System for Mobile Communication (GSM) and Global Positioning System (GPS). Keeping in view the importance of real-time notifications for safety related issues, we developed a fire-alarm system assisted by GSM and GPS technology. It is challenging to monitor homes at far off places. However, the availability of modern sensors and wireless technology have played an important role to deal with such issues efficiently. Moreover, recent improvements in the field of information technology have provided cost effective and efficient solutions. In this study, a low-cost smart fire alarm system is designed and implemented using Arduino microcontroller that continuously receives temperature and humidity signals form the sensors. In case of any emergency, the owner receives warning messages by GSM with the exact location of incident traced by GPS. To get accurate and improved results, a variable threshold alert algorithm is used for temperature compensation and accuracy.

GPS Receiver Position Augmentation Using Correntropy Kalman Filter in Low Latitude Terrain

If any Global Positioning System (GPS) receiver is operated in low latitude regions or urban canyons, the visibility further reduces. These system constraints lead to many challenges in providing precise GPS position accuracy over the Indian subcontinent. As a result, the standalone GPS accuracy does not meet the aircraft landing requirements, such as Category I (CAT-I) Precision Approaches. However, the required accuracy can be achieved by augmenting the GPS. Among all these issues, the predominant factors that significantly influence the receiver position accuracy are selecting a user/receiver position estimation algorithm. In this article, a novel method is proposed based on correntropy and designated as Correntropy Kalman Filter (CKF) for precise GPS applications and GPS Aided Geosynchronous equatorial orbit Augmented Navigation (GAGAN) based aircraft landings over the low latitude Indian subcontinent. The real-world GPS data collected from a dual-frequency GPS receiver located in the southern region of the Indian subcontinent (IISc), Bangalore with Lat/Long: 13.021°N/ 77.5°E) is used for the performance evaluation of the proposed algorithm. Results prove that the proposed CKF algorithm exhibits significant improvement (up to 34%) in position estimation compared to the traditional Kalman Filter.

Simple Methodology for the Development and Analysis of Local Driving Cycles Applied in the Study of Cars and Motorcycles in Recife, Brazil

Standard driving cycles are usually used to compare vehicles from distinct regions, and local driving cycles reproduce more realistic conditions in specific regions. In this article, we employed a simple methodology for developing local driving cycles and subsequently performed a kinematic and energy analysis. As an application, we employed the methodology for cars and motorcycles in Recife, Brazil. The speed profile was collected using a smartphone (1 Hz) validated against a high precision global positioning system (10 Hz), presenting a mean absolute error of 3 km/h. The driving cycles were thus developed using the micro-trip method. The kinematic analysis indicated that motorcycles had a higher average speed and acceleration (32.5 km/h, 0.84 m/s2) than cars (22.6 km/h, 0.55 m/s2). As a result of the energy analysis, it was found that inertia is responsible for most of the fuel consumption for both cars (59%) and motorcycles (41%), but for motorcycles the aerodynamic drag is also relevant (36%). With regards to fuel consumption, it was found that the standard driving cycle used in Brazil (FTP-75; 2.47 MJ/km for cars and 0.84 MJ/km for motorcycles) adequately represents the driving profile for cars (2.46 MJ/km), and to a lesser extent motorcycles (0.91 MJ/km) in off-peak conditions. Finally, we evaluated the influence of the vehicle category on energy consumption, obtaining a maximum difference of 38% between a 2.0 L sports utility vehicle and a 1.0 L hatchback.

PSO-LSSVR Assisted GPS/INS Positioning in Occlusion Region.

Satellite signals are easily lost in complex observation environments and high dynamic motion states, and the position and posture errors of pure inertial navigation quickly diverges with time. This paper therefore proposes a scheme of occlusion region navigation based on least squares support vector regression (LSSVR), and particle swarm optimization (PSO), used to seek the global optimal parameters. Firstly, the scheme uses the incremental output of GPS (Global Positioning System) and Inertial Navigation System (INS) when the observation is normal as the training output and the training input sample, and then uses PSO to optimize the regression parameters of LSSVR. When the satellite signal is unavailable, the trained mapping model is used to predict the GPS pseudo position. Secondly, the observed anomaly is detected by the test statistic in the integrated navigation solution filtering estimation, and the exponential fading adaptive factor is introduced to suppress the influence of the abnormal pseudo observation value. The results indicate that the algorithm can predict the higher precision GPS position increment, and can effectively judge some abnormal observations that may occur in the predicted value, and adjust the observed noise covariance to suppress the anomaly observation, which can effectively improve the continuity and reliability of the integrated navigation system in the occlusion region.

Accuracy analysis of GPS broadcast ephemeris in the 2036th GPS week

Satellite orbit error is one of main sources in Global Positioning System (GPS) receiver positioning error. Using broadcast ephemeris in navigation message, the receiver can calculate spatial position of GPS satellites, then combine pseudorange measurements and achieve positioning solution. In this work, taking broadcast ephemeris in the 2036th GPS week as an example, orbital position of the satellite with the pseudo-random-noise (PRN) code 4 is calculated. Furthermore, using GPS precision ephemeris as a reference, orbital error of the broadcast ephemeris for the PRN 4 satellite is investigated. The results show that the maximum difference of the satellite in three directions is 36 meters, 57 meters and 39 meters, respectively. The three-dimension distance deviating from precision ephemeris is at most 61 meters. The maximum deviation occurs only during certain time periods in the whole GPS week.

Covariance Analysis of Real-Time Precise GPS Orbit Estimated from Double-Differenced Carrier Phase Observations

The covariance of real-time global positioning system (GPS) orbits has been drawing attention in various fields such as user integrity, navigation performance improvement, and fault detection. The international global navigation satellite system (GNSS) service (IGS) provides real-time orbit standard deviations without correlations between the axes. However, without correlation information, the provided covariance cannot assure the performance of the orbit product, which would, in turn, causes significant problems in fault detection and user integrity. Therefore, we studied real-time GPS orbit covariance characteristics along various coordinates to effectively provide conservative covariance. To this end, the covariance and precise orbits are estimated by means of an extended Kalman filter using double-differenced carrier phase observations of 61 IGS reference stations. Furthermore, we propose a new method for providing covariance to minimize loss of correlation. The method adopted by the IGS, which neglects correlation, requires 4.5 times the size of the covariance to bind orbit errors. By comparison, our proposed method reduces this size from 4.5 to 1.3 using only one additional parameter. In conclusion, the proposed method effectively provides covariance to users.

Low-cost versus high-grade global navigation satellite system receivers: kinematic global positioning system–BeiDou navigation satellite system single-point positioning performance evaluation for vehicular urban navigation

Low-cost receivers have already entered the mass market over the past few years. The high-precision real-time kinematic and precise-point positioning evaluation based on low-cost receivers has been analyzed and verified by many other studies in the past. With the integration of the multiglobal navigation satellite system (GNSS) and advances in technology, low-cost GNSS receivers are expected to be widely used in vehicle navigation. To investigate the kinematic single-point positioning (SPP) performance of low-cost receivers, we first assembled a low-cost receiver that can receive both American global positioning system (GPS) L1 and Chinese BeiDou Navigation Satellite System (BDS) B1 signals simultaneously. Then, a vehicle-positioning experiment is conducted in Fuzhou, China. For comparison purposes, the assembled low-cost receiver and a higher-grade receiver are connected to a survey-grade antenna via a power divider. The positioning accuracy and position dilution of the precision of GPS, BDS, and GPD/BDS SPP with both receivers are compared and analyzed. The results indicate that the low-cost receiver can achieve horizontal precision better than 1 m in the combined GPS/BDS case, when the car is positioned in the urban main road and expressway. This result is competitive and similar to that of the higher-grade receiver. Moreover, although the positioning precision of the low-cost receiver is worse than that of the higher-grade receiver in the GPS-only and BDS-only SPP case, it outperforms the higher-grade receiver in terms of satellite tracking, especially for tracking GPS satellite.

Precision of continuous GPS velocities from statistical analysis of synthetic time series

Abstract. We use statistical analyses of synthetic position time series to estimate the potential precision of GPS (Global Positioning System) velocities. The synthetic series represent the standard range of noise, seasonal, and position offset characteristics, leaving aside extreme values. This analysis is combined with a new simple method for automatic offset detection that allows an automatic treatment of the massive dataset. Colored noise and the presence of offsets are the primary contributor to velocity variability. However, regression tree analyses show that the main factors controlling the velocity precision are first the duration of the series, second the presence of offsets, and third the noise level (dispersion and spectral index). Our analysis allows us to propose guidelines, which can be applied to actual GPS data, that constrain velocity precisions, characterized as a 95 % confidence limit of the velocity biases, based on simple parameters: (1) series durations over 8.0 years result in low-velocity biases in the horizontal (0.2 mm yr−1) and vertical (0.5 mm yr−1) components; (2) series durations of less than 4.5 years are not suitable for studies that require precisions lower than mm yr−1; (3) series of intermediate durations (4.5–8.0 years) are associated with an intermediate horizontal bias (0.6 mm yr−1) and a high vertical one (1.3 mm yr−1), unless they comprise no offset. Our results suggest that very long series durations (over 15–20 years) do not ensure a significantly lower bias compared to series of 8–10 years, due to the noise amplitude following a power-law dependency on the frequency. Thus, better characterizations of long-period GPS noise and pluri-annual environmental loads are critical to further improve GPS velocity precisions.

The Magnitude of Diurnal/Semidiurnal Atmospheric Tides (S1/S2) and Their Impacts on the Continuous GPS Coordinate Time Series

The site displacement due to diurnal and semidiurnal atmospheric tides (S1/S2) is often neglected in the routine precise GPS data processing. We recall the S1/S2 modeling method and show the magnitude of the S1/S2 tides under the Center of Mass (CM) frame. The results show that the annual amplitudes caused by both S1 and S2 tides exceed 1 mm for stations near the equator. The impact of S1/S2 on the 24-h Global Positioning System (GPS) solution is typically at the sub-mm level, and the scatter of the S1/S2 caused displacement difference increases with the decreasing latitude for northern hemisphere stations, among which the maximum Standard Deviation (STD) reaches up to 1.5 mm, 1 mm and 0.7 mm for the Up, East and North components, respectively, at low-latitude stations. We also find that 65% of the stations’ vertical velocity change caused by S1/S2 is larger than 1%, among which the maximum velocity variation rate reaches more than 40% for some coastal/island stations, while stations with the weighted root mean square reduced account for 65%, 39%, and 38% for the up, east, and north components respectively, in particular for most coastal/island stations. Furthermore, the S1/S2 correction could partly reduce the annual and the semi-annual signals of the global stacked vertical component together with the semi-annual amplitude of the east component. The power of some anomalous harmonics of 1.04 cycle per year also decreased a lot. These results further prove the benefits of S1/S2 correction in the precise GPS data processing.

Metrology Assessment of the Accuracy of Precipitable Water Vapor Estimates from GPS Data Acquisition in Tropical Areas: The Tahiti Case

High precision Global Positioning System (GPS) receivers, with the advantages of all-weather work and low cost, are now widely used to routinely monitor precipitable water (PW) vapor. They are so successful that the progressive phasing out of the costly and sparse in situ radio soundings (RS) is now a certainty. Nevertheless, the sub-daily to annual monitoring of high levels of the PW by GPS receivers in the tropics and the equatorial area still needs to be asserted in terms of metrology accuracy. This is the subject of this paper, which focuses on a tropical site located in mid-ocean (Tahiti). The metrology assessment was divided into two steps. Firstly, a GPS internal assessment, with an in-house processing based on the Bernese GNSS Software Version 5.2 and a comparison with the Center for Orbit Determination in Europe (CODE) products. Secondly, an external assessment, with a comparison with RS PW estimates. In contrast with previous works that only used PW estimates from the Integrated Global Radiosonde Archive (IGRA) website, we estimated the RS PW from the balloon raw data. This is especially important in tropical areas, where IGRA estimates only consider balloon measurements taken below approximately 5500 m. We show that, in our case, this threshold is one of the main sources of bias between GPS and RS estimates, and that the formula used to translate the GPS zenith wet delays (ZWD) to PW estimates also needs to be revisited for high level water vapor contents in the atmosphere.

Effects of age and reproductive status on individual foraging site fidelity in a long-lived marine predator.

Individual foraging specializations, where individuals use a small component of the population niche width, are widespread in nature with important ecological and evolutionary implications. In long-lived animals, foraging ability develops with age, but we know little about the ontogeny of individuality in foraging. Here we use precision global positioning system (GPS) loggers to examine how individual foraging site fidelity (IFSF), a common component of foraging specialization, varies between breeders, failed breeders and immatures in a long-lived marine predator—the northern gannet Morus bassanus. Breeders (aged 5+) showed strong IFSF: they had similar routes and were faithful to distal points during successive trips. However, centrally placed immatures (aged 2–3) were far more exploratory and lacked route or foraging site fidelity. Failed breeders were intermediate: some with strong fidelity, others being more exploratory. Individual foraging specializations were previously thought to arise as a function of heritable phenotypic differences or via social transmission. Our results instead suggest a third alternative—in long-lived species foraging sites are learned during exploratory behaviours early in life, which become canalized with age and experience, and refined where possible—the exploration-refinement foraging hypothesis. We speculate similar patterns may be present in other long-lived species and moreover that long periods of immaturity may be a consequence of such memory-based individual foraging strategies.

Solar flare forecasting model based on automatic feature extraction

Solar flares are outbursts in the solar atmosphere resulting from sudden release of magnetic energy. The associated high energy particles and radiation threaten the safety of astronauts, reduce the lifetime of satellites, disturb the radio communications and degrade the precision of Global Positioning System. The radiation reaches the Earth about 8 min, and high energy particles take about 30 min to reach the earth after a solar flare. So solar flare forecasting is critical for providing enough time to respond to the space weather effects. Up to now, many statistical and machine learning methods are used to build a solar flare forecasting model. A machine learning based solar flare forecasting model normally requires solar physicists to design a feature extractor which can transform the observational images of active regions into physical features, and then the relationships between the features and the solar flares are discovered by the machine leaning algorithm. The priori knowledge of the solar physicists is added into the solar flare forecasting model by designing the feature extractor. For most of the machine learning methods, the hard part is what kinds of features should be extracted from the raw data. Considerable solar physicists spend a lot of time extracting the physical parameters from observational data of active regions. Deep learning method, which removes this manual step, can automatically discover useful patterns from the raw data and build a forecasting model. Instead of designing the feature extractor by solar physicists, we learn a solar flare forecasting model from magnetogram pixels by using deep learning method. We use Caffe, which is a deep learning framework developed by the Berkeley Vision and Learning Center, to build a convolutional neural network for solar flare forecasting. In order to compare the performance of proposed forecasting model with that of the forecasting model built by using traditional machine learning method, we build the other solar flare forecasting model based on the same dataset. In the traditional forecasting model, physical parameters designed by the solar physicist are extracted from the magnetogram of active regions, and then these parameters are fed to the forecasting model. We build a traditional forecasting model by multilayer neural networks. For convenience, the solar flare forecasting model built by using deep learning method is called deep model, and the solar flare forecasting model built by using the traditional multilayer neutral networks is called traditional model. Using the same testing data, the performances of the deep model and the traditional model are evaluated and compared. We find that the performance of the deep model is little better than that of the traditional model. The results confirm that the deep model can automatically learn solar flare forecasting features from magnetograms of active regions. This is our first time to automatically learn the forecasting patterns for solar flares from raw data instead of designing the physical patterns by solar physicists. The effectiveness of the deep learning method for the solar flare forecasting is validated. In the future, the deep learning method can be used to automatically discover the solar flare forecasting patterns from the vector magnetograms or the extreme ultraviolet images of active regions.

Hybridized centroid technique for 3D Molodensky-Badekas coordinate transformation in the Ghana geodetic reference network using total least squares approach

The Molodensky-Badekas model is one of the similarity transformation models used in Ghana for transferring Global Positioning System (GPS) coordinates from the geocentric World Geodetic System 1984 (WGS 84) ellipsoid to the local non-geocentric coordinate system, and vice versa. The objective of the Molodensky-Badekas model is to introduce a centroid to cater for the correlation that exists between the parameters when used over a small portion on the earth surface. However, the Molodensky-Badekas model performance depends on a particular centroid method adopted and the adjustment technique used. By virtue of literature covered, it was realised that the arithmetic mean centroid has been the most widely used. In view of this, the present study developed and tested two new hybrid centroid techniques known as the harmonic-quadratic mean and arithmetic-quadratic mean centroids. The proposed hybrid approaches were compared with the geometric mean, harmonic mean, median, quadratic mean and arithmetic mean. In addition, the Total Least Squares (TLS) technique was used to compute the transformation parameters with varying centroid techniques to investigate and assess their accuracies in precise GPS datum transformation parameters estimation within the Ghana Geodetic Reference Network. Statistical indicators such as Mean Error (ME), Mean Squared Error (MSE), Standard Deviation (SD), and Mean Horizontal Position Error (MHPE) were used to assess the centroid techniques performance. The results attained show that the Harmonic-Quadratic Mean produced reliable coordinate transformation results within the Ghana geodetic reference network and thus could serve as practical alternative technique to the frequently used arithmetic mean. Keywords: Coordinate transformation, Molodensky-Badekas model, Centroid, Total Least Squares

Assessment of second- and third-order ionospheric effects on regional networks: case study in China with longer CMONOC GPS coordinate time series

Higher-order ionospheric (HOI) delays are one of the principal technique-specific error sources in precise global positioning system analysis and have been proposed to become a standard part of precise GPS data processing. In this research, we apply HOI delay corrections to the Crustal Movement Observation Network of China’s (CMONOC) data processing (from January 2000 to December 2013) and furnish quantitative results for the effects of HOI on CMONOC coordinate time series. The results for both a regional reference frame and global reference frame are analyzed and compared to clarify the HOI effects on the CMONOC network. We find that HOI corrections can effectively reduce the semi-annual signals in the northern and vertical components. For sites with lower semi-annual amplitudes, the average decrease in magnitude can reach 30 and 10 % for the northern and vertical components, respectively. The noise amplitudes with HOI corrections and those without HOI corrections are not significantly different. Generally, the HOI effects on CMONOC networks in a global reference frame are less obvious than the results in the regional reference frame, probably because the HOI-induced errors are smaller in comparison to the higher noise levels seen when using a global reference frame. Furthermore, we investigate the combined contributions of environmental loading and HOI effects on the CMONOC stations. The largest loading effects on the vertical displacement are found in the mid- to high-latitude areas. The weighted root mean square differences between the corrected and original weekly GPS height time series of the loading model indicate that the mass loading adequately reduced the scatter on the CMONOC height time series, whereas the results in the global reference frame showed better agreements between the GPS coordinate time series and the environmental loading. When combining the effects of environmental loading and HOI corrections, the results with the HOI corrections reduced the scatter on the observed GPS height coordinates better than the height when estimated without HOI corrections, and the combined solutions in the regional reference frame indicate more preferred improvements. Therefore, regional reference frames are recommended to investigate the HOI effects on regional networks.

Assessing Digital Elevation Model Uncertainty Using GPS Survey Data

AbstractThe use of terrain and elevation data is critical for a number of applications in science and engineering. Typically, the quality of digital elevation models (DEMs) is assessed using external and independent point data sources to arrive at an overall RMS value for the errors. The utility of such a single-valued overall assessment depends on the spatial extent of the area under consideration and the terrain variability (both over time and space), as well as the application requirements. This paper aimed to understand the suite of parameters that are important to consider in deriving a DEM error budget. Specifically, terrain slope, land-cover type, information loss, and data measurement schemes were investigated. A region in western Canada spanning the Rocky Mountains was used to numerically quantify errors using two Global Positioning System (GPS) datasets: precise point positioning (PPP) profiles and GPS on benchmarks. Three digital elevation models [Advanced Spaceborne Thermal Emission and Reflec...

Evaluation of GPS Standard Point Positioning with Various Ionospheric Error Mitigation Techniques

AbstractThe present paper investigates accuracy of single and dual-frequency Global Positioning System (GPS) standard point positioning solutions employing different ionosphere error mitigation techniques. The total electron content (TEC) in the ionosphere is the prominent delay error source in GPS positioning, and its elimination is essential for obtaining a relatively precise positioning solution. The estimated delay error from different ionosphere models and maps, such as Klobuchar model, global ionosphere models, and vertical TEC maps are compared with the locally derived ionosphere error following the ion density and frequency dependence with delay error. Finally, the positional accuracy of the single and dual-frequency GPS point positioning solutions are probed through different ionospheric mitigation methods including exploitation of models, maps, and ionosphere-free linear combinations and removal of higher order ionospheric effects. The results suggest the superiority of global ionosphere maps for single-frequency solution, whereas for the dual-frequency measurement the ionosphere-free linear combination with prior removal of higher-order ionosphere effects from global ionosphere maps and geomagnetic reference fields resulted in improved positioning quality among the chosen mitigation techniques. Conspicuously, the susceptibility of height component to different ionospheric mitigation methods are demonstrated in this study which may assist the users in selecting appropriate technique for precise GPS positioning measurements.